diff --git a/.editorconfig b/.editorconfig
index 66678e3..4e00f8f 100644
--- a/.editorconfig
+++ b/.editorconfig
@@ -8,7 +8,7 @@ charset = utf-8
 trim_trailing_whitespace = true
 insert_final_newline = true
 
-[{*.{yml,yaml,toml},.cruft.json}]
+[*.{yml,yaml,toml}]
 indent_size = 2
 
 [Makefile]
diff --git a/.env.example b/.env.example
new file mode 100644
index 0000000..38e8192
--- /dev/null
+++ b/.env.example
@@ -0,0 +1,13 @@
+# Copy this file to `.env` and fill in your own secrets.
+#
+#     cp .env.example .env
+#
+# `.env` is gitignored and must NEVER be committed. Only this example file,
+# with placeholder values, belongs in version control. If you ever paste a
+# real key into a tracked file by mistake, rotate it immediately in the
+# provider's dashboard.
+
+# API keys for LLM-based tooling (optional — only if your analysis uses them)
+OPENAI_API_KEY="sk-..."
+GEMINI_API_KEY="..."
+ANTHROPIC_API_KEY="sk-ant-..."
diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md
index 71c7629..2dfdcea 100644
--- a/.github/ISSUE_TEMPLATE/bug_report.md
+++ b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -33,7 +33,7 @@ assignees: ""
 <details> <summary> Versions </summary>
 
 ```pytb
-# Paste the ouput of tradeseq.__version__ and all relevant versions here
+# Paste the output of `session_info2.session_info()` (or your package's __version__) and all relevant versions here
 ```
 
 </details>
diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
index dc066db..944e99e 100644
--- a/.github/pull_request_template.md
+++ b/.github/pull_request_template.md
@@ -1,18 +1,18 @@
 ## Changes
 
-<!-- Please remove section if this PR does change an existing feature -->
+<!-- Please remove this section if this PR does not change an existing feature -->
 
 -   ...
 
 ## Bug fixes
 
-<!-- Please give section if this PR does not fix any bugs -->
+<!-- Please remove this section if this PR does not fix any bugs -->
 
 -   ...
 
 ## New
 
-<!-- Please give section if this PR does not implement a new feature -->
+<!-- Please remove this section if this PR does not implement a new feature -->
 
 -   ...
 
diff --git a/.github/workflows/lint.yaml b/.github/workflows/lint.yaml
index e5750c6..ad06492 100644
--- a/.github/workflows/lint.yaml
+++ b/.github/workflows/lint.yaml
@@ -21,8 +21,9 @@ jobs:
           fetch-depth: 0
       - uses: prefix-dev/setup-pixi@v0.8.0
         with:
-          pixi-version: v0.40.0
+          pixi-version: v0.60.0
           cache: true
+          frozen: true
       - name: Run pre-commit checks
         run: pixi run pre-commit run --all-files
       - name: Verify notebooks contain no outputs
diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml
index 086f4c4..7485677 100644
--- a/.github/workflows/test.yaml
+++ b/.github/workflows/test.yaml
@@ -24,7 +24,8 @@ jobs:
           fetch-depth: 0
       - uses: prefix-dev/setup-pixi@v0.8.0
         with:
-          pixi-version: v0.40.0
+          pixi-version: v0.60.0
           cache: true
+          frozen: true
       - name: Run tests
         run: pixi run test
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index e33f882..e7868e5 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -10,7 +10,6 @@ repos:
     rev: v2.2.3
     hooks:
       - id: biome-format
-        exclude: ^\.cruft\.json$ # inconsistent indentation with cruft - file never to be modified manually.
   - repo: https://github.com/tox-dev/pyproject-fmt
     rev: v2.6.0
     hooks:
@@ -33,15 +32,4 @@ repos:
         args: [--fix=lf]
       - id: trailing-whitespace
       - id: check-case-conflict
-      # Check that there are no merge conflicts (could be generated by template sync)
       - id: check-merge-conflict
-        args: [--assume-in-merge]
-  - repo: local
-    hooks:
-      - id: forbid-to-commit
-        name: Don't commit rej files
-        entry: |
-          Cannot commit .rej files. These indicate merge conflicts that arise during automated template updates.
-          Fix the merge conflicts manually and remove the .rej files.
-        language: fail
-        files: '.*\.rej$'
diff --git a/README.md b/README.md
index 50ab3fd..11785c3 100644
--- a/README.md
+++ b/README.md
@@ -52,13 +52,32 @@ The URL depends on your authentication method:
 
 ### Step 3: Customize the template
 
-Before installing the environment, update these files with your project details:
+The template ships with a placeholder package name (`myanalysis`) and project
+name (`analysis-template`). Rename them in one shot with the included script
+(stdlib-only, so run it with plain `python` *before* installing the env):
+
+```bash
+python scripts/rename_package.py myproject
+# or set the Jupyter kernel display name explicitly:
+python scripts/rename_package.py myproject --display-name "My Project"
+```
+
+This renames `src/myanalysis/` → `src/myproject/` and updates every reference in
+`pyproject.toml`, `pixi.toml` (package + workspace + kernel name), `tests/`, and
+the notebooks under `analysis/`.
+
+Then finish by hand:
 
 | File | What to change |
 |------|----------------|
-| `src/myanalysis/` | **Rename this folder** to your project slug (e.g., `src/myproject/`) |
-| `pyproject.toml` | Update `name` to match your renamed folder |
-| `pixi.toml` | Update `name`, `description`, `authors`, kernel `display-name`, and `myanalysis` → your package name in `[pypi-dependencies]` |
+| `pixi.toml` | Update `[workspace]` `description` and `authors` |
+| `README.md` | Replace with your own project documentation (Step 6 / later) |
+
+> Doing it manually instead? The placeholder `myanalysis` appears in
+> `pyproject.toml`, the `src/myanalysis/` folder name, `pixi.toml`
+> (`[pypi-dependencies]`), `tests/test_basic.py`, and the demo notebook; the
+> project name `analysis-template` and the kernel `display-name` live in the
+> `pixi.toml` `[tasks]` `install-kernel` command. The script handles all of them.
 
 ### Step 4: Set up the environment
 
@@ -100,7 +119,7 @@ git push
 
 ## 📊 Start Your Analysis
 
-- **Demo notebook**: Check out `analysis/demo_scRNA_workflow.ipynb` for a complete scRNA-seq workflow example using scanpy's PBMC 3k dataset.
+- **Demo notebook**: Check out `analysis/ML-2026-01-27_demo_scRNA_workflow.ipynb` for a complete scRNA-seq workflow example using scanpy's PBMC 3k dataset.
 - **New notebooks**: Copy `analysis/XX-2026-01-27_sample_notebook.ipynb` as a starting point. Follow the naming convention: `[INITIALS]-[YYYY]-[MM]-[DD]_description.ipynb`.
 - **Add your data**: Create folders under `data/` and register paths in `src/<your-package>/_constants.py`.
 - **Replace this README** with your project documentation once you're set up.
@@ -213,12 +232,50 @@ pre-commit run --all-files
 <details>
 <summary><strong>🖥️ GPU notes</strong></summary>
 
-| Platform | PyTorch | JAX |
-|----------|---------|-----|
-| **macOS** (Apple Silicon) | ✅ MPS acceleration | ❌ CPU only |
-| **Linux** (NVIDIA GPU) | ✅ CUDA | ✅ CUDA 12 |
+The **default** environment is CPU-only on every platform (on macOS, PyTorch
+still uses MPS automatically). This is what `pixi install` and CI use.
+
+GPU acceleration lives in a separate **`gpu`** environment that you opt into
+explicitly on a Linux/CUDA machine (e.g. ETH Euler):
+
+```bash
+pixi install -e gpu            # CUDA 12 build of JAX + rapids-singlecell
+pixi run -e gpu install-kernel # register a kernel for the gpu env
+pixi shell -e gpu              # or activate it interactively
+```
+
+| Environment | PyTorch | JAX | rapids-singlecell |
+|-------------|---------|-----|-------------------|
+| `default` (all platforms) | ✅ (MPS on macOS) | CPU | ❌ |
+| `gpu` (Linux + NVIDIA only) | ✅ CUDA | ✅ CUDA 12 | ✅ |
+
+> Keeping the GPU stack out of the default environment means CI and CPU-only
+> machines don't try to resolve unusable CUDA wheels. See
+> [rapids-singlecell](https://rapids-singlecell.readthedocs.io/).
+
+</details>
+
+<details>
+<summary><strong>🔑 Secrets & environment variables</strong></summary>
+
+Store API keys and other secrets in a `.env` file at the repo root. It is
+**gitignored** and must never be committed.
+
+```bash
+cp .env.example .env   # then fill in your real values
+```
+
+`.env.example` (tracked, placeholder values only) documents which variables the
+project expects. Load them in a notebook or script with, e.g.,
+[python-dotenv](https://github.com/theskumar/python-dotenv):
+
+```python
+from dotenv import load_dotenv
+load_dotenv()
+```
 
-The template auto-configures packages per platform. Linux also gets [rapids-singlecell](https://rapids-singlecell.readthedocs.io/) for GPU-accelerated analysis.
+If you ever paste a real key into a tracked file, rotate it immediately in the
+provider's dashboard — git history is hard to scrub.
 
 </details>
 
diff --git a/analysis/demo_scRNA_workflow.ipynb b/analysis/ML-2026-01-27_demo_scRNA_workflow.ipynb
similarity index 92%
rename from analysis/demo_scRNA_workflow.ipynb
rename to analysis/ML-2026-01-27_demo_scRNA_workflow.ipynb
index ffce349..e93671b 100644
--- a/analysis/demo_scRNA_workflow.ipynb
+++ b/analysis/ML-2026-01-27_demo_scRNA_workflow.ipynb
@@ -417,7 +417,9 @@
    "id": "31",
    "metadata": {},
    "source": [
-    "Now we use the downloaded model for annotation. "
+    "Now we use the downloaded model for annotation.\n",
+    "\n",
+    "⚠️ **Input scale matters.** CellTypist's `Immune_All_High` model expects expression that is **normalized to 10,000 counts per cell and log1p-transformed** (the same transform we applied in the preprocessing step). Annotating data on a different scale (e.g. raw counts, or `sc.pp.scale`-d/z-scored values) silently produces wrong labels. To stay robust we rebuild the expected input from the raw `counts` layer rather than assuming `adata.X` is still in that state."
    ]
   },
   {
@@ -427,9 +429,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Load and annotate\n",
+    "# Annotate on a fresh copy whose .X is guaranteed to be log1p(normalize_total(1e4)),\n",
+    "# rebuilt from the raw counts — independent of any later transforms on `adata.X`.\n",
+    "adata_celltypist = adata.copy()\n",
+    "adata_celltypist.X = adata_celltypist.layers[\"counts\"].copy()\n",
+    "sc.pp.normalize_total(adata_celltypist, target_sum=1e4)\n",
+    "sc.pp.log1p(adata_celltypist)\n",
+    "\n",
     "model = models.Model.load(model=\"Immune_All_High.pkl\")\n",
-    "predictions = celltypist.annotate(adata, model=model, majority_voting=True)"
+    "predictions = celltypist.annotate(adata_celltypist, model=model, majority_voting=True)"
    ]
   },
   {
diff --git a/data/example_dataset/README.md b/data/example_dataset/README.md
index d1110bb..8bc566d 100644
--- a/data/example_dataset/README.md
+++ b/data/example_dataset/README.md
@@ -1,5 +1,6 @@
 # Dataset structure
 
 -   `raw`: Raw state of the data we received.
--   `processed`: Processed data.
+-   `processed`: Processed / intermediate data.
+-   `resources`: Reference data, gene sets, annotations.
 -   `results`: Any results we compute for this dataset.
diff --git a/pixi.lock b/pixi.lock
index 2e16a76..048c3ad 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,6 +1,699 @@
 version: 6
 environments:
   default:
+    channels:
+    - url: https://conda.anaconda.org/conda-forge/
+    indexes:
+    - https://pypi.org/simple
+    options:
+      pypi-prerelease-mode: if-necessary-or-explicit
+    packages:
+      linux-64:
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/_python_abi3_support-1.0-hd8ed1ab_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.2-h39aace5_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.6-hb03c661_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.1.4-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cpython-3.12.12-py312hd8ed1ab_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-mpi_openmpi_h76e6d66_11.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/geos-3.14.1-h480dda7_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/hdf5-1.14.6-mpi_openmpi_h106f004_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/hypre-2.32.0-mpi_openmpi_h398ea61_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.2-h33c6efd_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-hb9d3cd8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/krb5-1.21.3-h659f571_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.45-default_hbd61a6d_105.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libaec-1.1.5-h088129d_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libamd-3.3.3-h456b2da_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-7_hc00574d_netlib.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbtf-2.3.2-hf02c80a_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcamd-3.3.3-hf02c80a_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.77-h3ff7636_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.11.0-7_h8e06fc2_netlib.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libccolamd-3.3.4-hf02c80a_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcholmod-5.3.1-h9cf07ce_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcolamd-3.3.4-hf02c80a_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcurl-8.18.0-h4e3cde8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20250104-pl5321h7949ede_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-hd590300_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.12-hf998b51_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.3-hecca717_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfabric-2.4.0-ha770c72_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfabric1-2.4.0-h8f87c3e_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-15.2.0-h69a702a_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.2.0-h68bc16d_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.12.2-default_hafda6a7_1000.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.18-h3b78370_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libklu-2.3.5-h95ff59c_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.11.0-7_h8876d29_netlib.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.2-hb03c661_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.67.0-had1ee68_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libnl-3.11.0-hb9d3cd8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hb9d3cd8_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libpmix-5.0.8-h9b03745_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libptscotch-7.0.10-int32_ha94cade_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libscotch-7.0.10-int32_h865694f_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libspqr-4.3.4-h23b7119_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.51.2-hf4e2dac_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.11.1-hcf80075_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-15.2.0-hdf11a46_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libsuitesparseconfig-7.10.1-h901830b_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.10-hd0affe5_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libudev1-257.10-hd0affe5_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libumfpack-6.3.5-h873dde6_7100101.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.41.3-h5347b49_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcrypt-4.4.36-hd590300_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libxml2-16-2.15.1-hca6bf5a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.15.1-he237659_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/metis-5.1.0-hd0bcaf9_1007.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/mpi-1.0.1-openmpi.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/mumps-include-5.8.1-h158ef2a_4.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/mumps-mpi-5.8.1-hcc12995_4.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/numpy-2.1.3-py312h58c1407_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/openmpi-5.0.8-h611b0e2_111.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.0-h26f9b46_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/parmetis-4.0.3-h02de7a9_1007.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/petsc-3.24.3-real_h326748a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/petsc4py-3.24.3-np2py310h90edcb8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.12.12-hd63d673_2_cpython.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/python-gil-3.12.12-hd8ed1ab_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.12-8_cp312.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/rdma-core-61.0-h192683f_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/scalapack-2.2.0-hf7e2fd8_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/shapely-2.1.2-py312h383787d_2.conda
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+  - nvidia-cuda-cupti-cu12==12.8.90.* ; (sys_platform == 'linux' and extra == 'cupti') or (sys_platform == 'win32' and extra == 'cupti')
+  - nvidia-curand-cu12==10.3.9.90.* ; (sys_platform == 'linux' and extra == 'curand') or (sys_platform == 'win32' and extra == 'curand')
+  - nvidia-cusolver-cu12==11.7.3.90.* ; (sys_platform == 'linux' and extra == 'cusolver') or (sys_platform == 'win32' and extra == 'cusolver')
+  - nvidia-cusparse-cu12==12.5.8.93.* ; (sys_platform == 'linux' and extra == 'cusparse') or (sys_platform == 'win32' and extra == 'cusparse')
+  - nvidia-cuda-cuxxfilt-cu12==12.8.90.* ; (sys_platform == 'linux' and extra == 'cuxxfilt') or (sys_platform == 'win32' and extra == 'cuxxfilt')
+  - nvidia-npp-cu12==12.3.3.100.* ; (sys_platform == 'linux' and extra == 'npp') or (sys_platform == 'win32' and extra == 'npp')
+  - nvidia-cuda-nvcc-cu12==12.8.93.* ; (sys_platform == 'linux' and extra == 'nvcc') or (sys_platform == 'win32' and extra == 'nvcc')
+  - nvidia-nvfatbin-cu12==12.8.90.* ; (sys_platform == 'linux' and extra == 'nvfatbin') or (sys_platform == 'win32' and extra == 'nvfatbin')
+  - nvidia-nvjitlink-cu12==12.8.93.* ; (sys_platform == 'linux' and extra == 'nvjitlink') or (sys_platform == 'win32' and extra == 'nvjitlink')
+  - nvidia-nvjpeg-cu12==12.3.5.92.* ; (sys_platform == 'linux' and extra == 'nvjpeg') or (sys_platform == 'win32' and extra == 'nvjpeg')
+  - nvidia-nvml-dev-cu12==12.8.90.* ; (sys_platform == 'linux' and extra == 'nvml') or (sys_platform == 'win32' and extra == 'nvml')
+  - nvidia-cuda-nvrtc-cu12==12.8.93.* ; (sys_platform == 'linux' and extra == 'nvrtc') or (sys_platform == 'win32' and extra == 'nvrtc')
+  - nvidia-nvtx-cu12==12.8.90.* ; (sys_platform == 'linux' and extra == 'nvtx') or (sys_platform == 'win32' and extra == 'nvtx')
+  - nvidia-cuda-opencl-cu12==12.8.90.* ; (sys_platform == 'linux' and extra == 'opencl') or (sys_platform == 'win32' and extra == 'opencl')
+  - nvidia-cuda-profiler-api-cu12==12.8.90.* ; (sys_platform == 'linux' and extra == 'profiler') or (sys_platform == 'win32' and extra == 'profiler')
+  - nvidia-cuda-sanitizer-api-cu12==12.8.93.* ; (sys_platform == 'linux' and extra == 'sanitizer') or (sys_platform == 'win32' and extra == 'sanitizer')
+- pypi: https://files.pythonhosted.org/packages/57/b2/453099f5f3b698d7d0eab38916aac44c7f76229f451709e2eb9db6615dcd/cuda_toolkit-13.0.2-py2.py3-none-any.whl
   name: cuda-toolkit
   version: 13.0.2
   sha256: b198824cf2f54003f50d64ada3a0f184b42ca0846c1c94192fa269ecd97a66eb
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   - nvidia-cuda-profiler-api==13.0.85.* ; (sys_platform == 'linux' and extra == 'profiler') or (sys_platform == 'win32' and extra == 'profiler')
   - nvidia-cuda-sanitizer-api==13.0.85.* ; (sys_platform == 'linux' and extra == 'sanitizer') or (sys_platform == 'win32' and extra == 'sanitizer')
+- pypi: https://pypi.nvidia.com/cudf-cu12/cudf_cu12-26.2.1-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
+  name: cudf-cu12
+  version: 26.2.1
+  sha256: 23c0f10714903d522c8c444107b5239bdbfa6878873e37782cf41d53bcc21a75
+  requires_dist:
+  - cachetools
+  - cuda-python>=12.9.2,<13.0
+  - cuda-toolkit[nvcc,nvrtc]==12.*
+  - cupy-cuda12x>=13.6.0
+  - fsspec>=0.6.0
+  - libcudf-cu12==26.2.*
+  - numba-cuda[cu12]>=0.22.2,<0.23.0
+  - numba>=0.60.0,<0.62.0
+  - numpy>=1.23,<3.0
+  - nvtx>=0.2.1
+  - packaging
+  - pandas>=2.0,<2.4.0
+  - pyarrow>=15.0.0,!=17.0.0 ; platform_machine == 'aarch64'
+  - pyarrow>=15.0.0 ; platform_machine == 'x86_64'
+  - pylibcudf-cu12==26.2.*
+  - rich
+  - rmm-cu12==26.2.*
+  - typing-extensions>=4.0.0
+  - aiobotocore>=2.2.0,<3 ; extra == 'test'
+  - boto3>=1.21.21 ; extra == 'test'
+  - botocore>=1.24.21 ; extra == 'test'
+  - cramjam ; extra == 'test'
+  - fastavro>=0.22.9 ; extra == 'test'
+  - hypothesis>=6.131.7 ; extra == 'test'
+  - msgpack ; extra == 'test'
+  - pytest ; extra == 'test'
+  - pytest-benchmark ; extra == 'test'
+  - pytest-cases>=3.8.2 ; extra == 'test'
+  - pytest-cov ; extra == 'test'
+  - pytest-xdist ; extra == 'test'
+  - s3fs>=2022.3.0 ; extra == 'test'
+  - scipy ; extra == 'test'
+  - tzdata ; extra == 'test'
+  - zstandard ; extra == 'test'
+  - hypothesis>=6.131.7 ; extra == 'pandas-tests'
+  - ipython ; extra == 'pandas-tests'
+  - pandas[clipboard,compression,computation,excel,feather,fss,hdf5,html,output-formatting,parquet,performance,plot,pyarrow,spss,test,xml] ; extra == 'pandas-tests'
+  - pytest-reportlog ; extra == 'pandas-tests'
+  - certifi ; extra == 'cudf-pandas-tests'
+  - ipython ; extra == 'cudf-pandas-tests'
+  - jupyter-client ; extra == 'cudf-pandas-tests'
+  - nbconvert ; extra == 'cudf-pandas-tests'
+  - nbformat ; extra == 'cudf-pandas-tests'
+  - openpyxl ; extra == 'cudf-pandas-tests'
+  - pytest-rerunfailures!=16.0.0 ; extra == 'cudf-pandas-tests'
+  requires_python: '>=3.10'
+- pypi: https://pypi.nvidia.com/cugraph-cu12/cugraph_cu12-26.2.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
+  name: cugraph-cu12
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+  sha256: 2ff7af2dcbd71cbca677f17c8e2b14c940a36e3ed635304cf430d1ff1c4c2450
+  requires_dist:
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+  - cupy-cuda12x>=13.6.0
+  - dask-cuda==26.2.*
+  - dask-cudf-cu12==26.2.*
+  - fsspec[http]>=0.6.0
+  - libcugraph-cu12==26.2.*
+  - numba>=0.60.0,<0.62.0
+  - numpy>=1.23,<3.0
+  - pylibcudf-cu12==26.2.*
+  - pylibcugraph-cu12==26.2.*
+  - pylibraft-cu12==26.2.*
+  - raft-dask-cu12==26.2.*
+  - rapids-dask-dependency==26.2.*
+  - rmm-cu12==26.2.*
+  - ucxx-cu12==0.48.*
+  - certifi ; extra == 'test'
+  - networkx>=2.5.1 ; extra == 'test'
+  - numpy>=1.23,<3.0 ; extra == 'test'
+  - packaging ; extra == 'test'
+  - pandas ; extra == 'test'
+  - pytest-benchmark ; extra == 'test'
+  - pytest-cov ; extra == 'test'
+  - pytest-xdist ; extra == 'test'
+  - pytest<9.0.0 ; extra == 'test'
+  - python-louvain ; extra == 'test'
+  - scikit-learn>=0.23.1 ; extra == 'test'
+  - scipy ; extra == 'test'
+  requires_python: '>=3.10'
+- pypi: https://pypi.nvidia.com/cuml-cu12/cuml_cu12-26.2.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
+  name: cuml-cu12
+  version: 26.2.0
+  sha256: 7eeb6f3dda78e0172c88d4eb9a927ae08efb3307631b4d3acb863c98a1718472
+  requires_dist:
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+  - cuda-toolkit[cublas,cufft,curand,cusolver,cusparse]==12.*
+  - cudf-cu12==26.2.*
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+  - joblib>=0.11
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+  - numba>=0.60.0,<0.62.0
+  - numpy>=1.23,<3.0
+  - packaging
+  - pylibraft-cu12==26.2.*
+  - rich
+  - rmm-cu12==26.2.*
+  - scikit-learn>=1.5
+  - scipy>=1.13.0
+  - treelite>=4.6.1,<5.0.0
+  - certifi ; extra == 'test'
+  - cython>=3.0.0,<3.2.0 ; extra == 'test'
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+  - hypothesis>=6.0,<7 ; extra == 'test'
+  - ipython>=7.32.0 ; extra == 'test'
+  - nltk ; extra == 'test'
+  - numpydoc<1.9 ; extra == 'test'
+  - nvidia-ml-py>=12 ; extra == 'test'
+  - pynndescent ; extra == 'test'
+  - pytest-benchmark ; extra == 'test'
+  - pytest-cases ; extra == 'test'
+  - pytest-cov ; extra == 'test'
+  - pytest-xdist ; extra == 'test'
+  - pytest<9.0 ; extra == 'test'
+  - pyyaml ; extra == 'test'
+  - scikit-learn>=1.5 ; extra == 'test'
+  - seaborn ; extra == 'test'
+  - statsmodels ; extra == 'test'
+  - umap-learn==0.5.7 ; extra == 'test'
+  - xgboost-cu12>=2.1.0 ; extra == 'test'
+  - dask-cudf-cu12==26.2.* ; extra == 'dask'
+  - raft-dask-cu12==26.2.* ; extra == 'dask'
+  - rapids-dask-dependency==26.2.* ; extra == 'dask'
+  - dask-cuda==26.2.* ; extra == 'test-dask'
+  - dask-ml>=2024 ; extra == 'test-dask'
+  requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/f6/6e/dc03c1ddc940f33b3d32803898e2fdae5c9538a2127a25f499494c84b183/cupy_cuda12x-14.1.1-cp312-cp312-manylinux2014_x86_64.whl
+  name: cupy-cuda12x
+  version: 14.1.1
+  sha256: a1138f20080489a46209291498cd12f792226d0a57d50c64a586c162a875a069
+  requires_dist:
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+  - cuda-pathfinder==1.*,>=1.3.4
+  - scipy>=1.14,<1.17 ; extra == 'all'
+  - cython>=3 ; extra == 'all'
+  - optuna>=2.0 ; extra == 'all'
+  - packaging ; extra == 'test'
+  - pytest>=7.2 ; extra == 'test'
+  - hypothesis>=6.37.2,<6.55.0 ; extra == 'test'
+  - mpmath ; extra == 'test'
+  - cuda-toolkit[cublas,cudart,cufft,curand,cusolver,cusparse,nvrtc]==12.* ; extra == 'ctk'
+  requires_python: '>=3.10'
+- pypi: https://pypi.nvidia.com/cuvs-cu12/cuvs_cu12-26.2.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
+  name: cuvs-cu12
+  version: 26.2.0
+  sha256: ef83970c7b44de89247676b231a56888b57370a6f13b0afd19e962247db6647e
+  requires_dist:
+  - cuda-python>=12.9.2,<13.0
+  - libcuvs-cu12==26.2.*
+  - numpy>=1.23,<3.0
+  - pylibraft-cu12==26.2.*
+  - cupy-cuda12x>=13.6.0 ; extra == 'test'
+  - pytest-cov ; extra == 'test'
+  - pytest<9.0.0 ; extra == 'test'
+  - scikit-learn ; extra == 'test'
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl
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   - pytest-xdist ; extra == 'test'
   - pre-commit ; extra == 'test'
   requires_python: '>=3.10'
+- pypi: https://pypi.nvidia.com/dask-cuda/dask_cuda-26.2.0-py3-none-manylinux_2_28_aarch64.manylinux_2_28_x86_64.whl
+  name: dask-cuda
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+  - nvidia-ml-py>=12
+  - pandas>=1.3
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+  - numpydoc>=1.1.0 ; extra == 'docs'
+  - sphinx ; extra == 'docs'
+  - sphinx-click>=2.7.1 ; extra == 'docs'
+  - sphinx-rtd-theme>=0.5.1 ; extra == 'docs'
+  - cuda-core[cu12]==0.3.* ; extra == 'cu12'
+  - numba-cuda[cu12]>=0.22.1,<0.23.0 ; extra == 'cu12'
+  - cuda-core[cu13]==0.3.* ; extra == 'cu13'
+  - numba-cuda[cu13]>=0.22.1,<0.23.0 ; extra == 'cu13'
+  - pytest ; extra == 'test'
+  - pytest-cov ; extra == 'test'
+  - pytest-rerunfailures!=16.0.0 ; extra == 'test'
+  - pytest-timeout ; extra == 'test'
+  - cudf-cu12==26.2.* ; extra == 'test-cu12'
+  - dask-cudf-cu12==26.2.* ; extra == 'test-cu12'
+  - distributed-ucxx-cu12==0.48.* ; extra == 'test-cu12'
+  - kvikio-cu12==26.2.* ; extra == 'test-cu12'
+  - cudf-cu13==26.2.* ; extra == 'test-cu13'
+  - dask-cudf-cu13==26.2.* ; extra == 'test-cu13'
+  - distributed-ucxx-cu13==0.48.* ; extra == 'test-cu13'
+  - kvikio-cu13==26.2.* ; extra == 'test-cu13'
+  requires_python: '>=3.10'
+- pypi: https://pypi.nvidia.com/dask-cudf-cu12/dask_cudf_cu12-26.2.1-py3-none-any.whl
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+  - botocore>=1.24.21 ; extra == 'test'
+  - dask-cuda==26.2.* ; extra == 'test'
+  - pytest ; extra == 'test'
+  - pytest-cov ; extra == 'test'
+  - pytest-xdist ; extra == 'test'
+  - s3fs>=2022.3.0 ; extra == 'test'
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+  - sphinx-rtd-theme>=0.5.1 ; extra == 'docs'
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   timestamp: 1763157302873
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-  sha256: 2a79315fad4ac6317cb1b999f4e95b5910dccafd88545c2ce55b3551363749b2
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-  - anndata
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+  - anndata ; extra == 'datasets'
   - pooch ; extra == 'datasets'
   - pyyaml ; extra == 'datasets'
   - tqdm ; extra == 'datasets'
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+  - pytest-cov ; extra == 'cover'
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+  - mypy==1.18.* ; extra == 'type'
+  - importlib-metadata>=7.0.2 ; python_full_version < '3.10' and extra == 'type'
+  - jaraco-develop>=7.21 ; sys_platform != 'cygwin' and extra == 'type'
+  requires_python: '>=3.9'
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/slepc-3.25.1-real_h2a2c1a1_0.conda
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+  - mpich >=5.0,<6.0a0
+  - libblas >=3.9.0,<4.0a0
+  - petsc >=3.25.1,<3.26.0a0
+  - petsc * real_*
+  - liblapack >=3.9.0,<4.0a0
+  license: BSD-2-Clause
+  license_family: BSD
+  purls: []
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/slepc-3.25.1-real_h83378db_0.conda
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+  - scalapack >=2.2.0,<2.3.0a0
+  - mpich >=5.0,<6.0a0
+  - petsc >=3.25.1,<3.26.0a0
+  - petsc * real_*
+  license: BSD-2-Clause
+  license_family: BSD
+  purls: []
+  size: 9664071
+  timestamp: 1777962349336
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@@ -7760,6 +10657,29 @@ packages:
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   size: 562755
   timestamp: 1769023374683
+- conda: https://conda.anaconda.org/conda-forge/linux-64/slepc4py-3.25.1-np2py310hd586191_0.conda
+  noarch: python
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+  md5: 45c486789236331248871d346ccfd441
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+  - libgcc >=14
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+  - numpy >=1.21,<3
+  - mpich >=5.0,<6.0a0
+  - _python_abi3_support 1.*
+  - cpython >=3.10
+  - slepc >=3.25.1,<3.26.0a0
+  - slepc * real_*
+  constrains:
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+  license: BSD-2-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/slepc4py?source=hash-mapping
+  size: 567870
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 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/slepc4py-3.24.2-np2py310h0c2cbfb_0.conda
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   timestamp: 1769023482050
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/slepc4py-3.25.1-np2py310h41f7a1d_0.conda
+  noarch: python
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+  - petsc4py 3.25.*
+  - __osx >=11.0
+  - numpy >=1.21,<3
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+  - slepc * real_*
+  - mpich >=5.0,<6.0a0
+  - _python_abi3_support 1.*
+  - cpython >=3.10
+  constrains:
+  - mpi4py >=3.0.1
+  license: BSD-2-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/slepc4py?source=hash-mapping
+  size: 461619
+  timestamp: 1778053020631
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/superlu_dist-9.2.1-h5edd517_2.conda
+  sha256: 3f8014f5aefa0239ef9e2d24c25cfed93dae736d689d17297f732a7110a85987
+  md5: 2a54644dd61f8cb2ea5b72da15164f4a
+  depends:
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+  - libgcc >=14
+  - libgfortran5 >=14.3.0
+  - libgfortran
+  - __glibc >=2.17,<3.0.a0
+  - _openmp_mutex >=4.5
+  - liblapack >=3.9.0,<4.0a0
+  - metis >=5.1.0,<5.1.1.0a0
+  - libblas >=3.9.0,<4.0a0
+  - mpich >=5.0,<6.0a0
+  - parmetis >=4.0.3,<4.1.0a0
+  license: BSD-3-Clause
+  license_family: BSD
+  purls: []
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+  timestamp: 1781044951101
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@@ -8080,6 +11042,25 @@ packages:
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   timestamp: 1731327032505
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/superlu_dist-9.2.1-h339bd1a_2.conda
+  sha256: a58f3e9df4554e4d1b3dc4d75f5ddda2ee083cf0de74322ae5481f8b50794cb2
+  md5: 8a4c9191b939f39e776ec2313949d845
+  depends:
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+  - llvm-openmp >=19.1.7
+  - __osx >=11.0
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+  - libblas >=3.9.0,<4.0a0
+  - parmetis >=4.0.3,<4.1.0a0
+  - liblapack >=3.9.0,<4.0a0
+  - mpich >=5.0,<6.0a0
+  - metis >=5.1.0,<5.1.1.0a0
+  license: BSD-3-Clause
+  license_family: BSD
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   sha256: 15ccc861ac51c53696de0a5d6d4607f99c210739caf987b5d2054f3efed429d8
   requires_python: '>=3.9'
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+  name: torch
+  version: 2.10.0
+  sha256: 98c01b8bb5e3240426dcde1446eed6f40c778091c8544767ef1168fc663a05a6
+  requires_dist:
+  - filelock
+  - typing-extensions>=4.10.0
+  - setuptools ; python_full_version >= '3.12'
+  - sympy>=1.13.3
+  - networkx>=2.5.1
+  - jinja2
+  - fsspec>=0.8.5
+  - cuda-bindings==12.9.4 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cuda-nvrtc-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cuda-runtime-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cuda-cupti-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cudnn-cu12==9.10.2.21 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cublas-cu12==12.8.4.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cufft-cu12==11.3.3.83 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-curand-cu12==10.3.9.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cusolver-cu12==11.7.3.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cusparse-cu12==12.5.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cusparselt-cu12==0.7.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-nccl-cu12==2.27.5 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-nvshmem-cu12==3.4.5 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-nvtx-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-nvjitlink-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - nvidia-cufile-cu12==1.13.1.3 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - triton==3.6.0 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+  - optree>=0.13.0 ; extra == 'optree'
+  - opt-einsum>=3.3 ; extra == 'opt-einsum'
+  - pyyaml ; extra == 'pyyaml'
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/6f/8b/69e3008d78e5cee2b30183340cc425081b78afc5eff3d080daab0adda9aa/torch-2.11.0-cp312-cp312-macosx_11_0_arm64.whl
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   - pytest-mypy-testing ; extra == 'test'
   - pytest>=7.0,<8.2 ; extra == 'test'
   requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/a8/a2/ac3aad5c77f85f47890dd929b2690c2ba3794ebcbb5384c19aa28d222066/treelite-4.7.0-py3-none-manylinux2014_x86_64.whl
+  name: treelite
+  version: 4.7.0
+  sha256: d616f1df2b8c7c6497cda2b8434fbcefe07fa897d269bdde3b48b11fd62393d9
+  requires_dist:
+  - numpy
+  - packaging
+  - scipy
+  - scikit-learn ; extra == 'scikit-learn'
+  - hypothesis ; extra == 'testing'
+  - pandas ; extra == 'testing'
+  - pytest ; extra == 'testing'
+  - scikit-learn ; extra == 'testing'
+  requires_python: '>=3.8'
+- pypi: https://files.pythonhosted.org/packages/ab/a8/cdf8b3e4c98132f965f88c2313a4b493266832ad47fb52f23d14d4f86bb5/triton-3.6.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
+  name: triton
+  version: 3.6.0
+  sha256: 74caf5e34b66d9f3a429af689c1c7128daba1d8208df60e81106b115c00d6fca
+  requires_dist:
+  - importlib-metadata ; python_full_version < '3.10'
+  - cmake>=3.20,<4.0 ; extra == 'build'
+  - lit ; extra == 'build'
+  - autopep8 ; extra == 'tests'
+  - isort ; extra == 'tests'
+  - numpy ; extra == 'tests'
+  - pytest ; extra == 'tests'
+  - pytest-forked ; extra == 'tests'
+  - pytest-xdist ; extra == 'tests'
+  - scipy>=1.7.1 ; extra == 'tests'
+  - llnl-hatchet ; extra == 'tests'
+  - matplotlib ; extra == 'tutorials'
+  - pandas ; extra == 'tutorials'
+  - tabulate ; extra == 'tutorials'
+  requires_python: '>=3.10,<3.15'
 - pypi: https://files.pythonhosted.org/packages/c4/6f/fb96d15db6f36d6eae4cafb998c2e0353bf59d7c4ea1662d7497f269134a/triton-3.7.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
   name: triton
   version: 3.7.1
@@ -8534,6 +11582,41 @@ packages:
   purls: []
   size: 7801740
   timestamp: 1769197798676
+- conda: https://conda.anaconda.org/conda-forge/linux-64/ucx-1.20.1-hbe80e26_0.conda
+  sha256: 8f0ac4a92e4674eb4c87cdfc59d2fc7c2d0d1696689202eeb62ef715d82ce711
+  md5: 7d06bc10996e75c90b8cd7631b5dcf6c
+  depends:
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+  - _openmp_mutex >=4.5
+  - libgcc >=14
+  - libstdcxx >=14
+  - rdma-core >=61.0
+  constrains:
+  - cuda-version >=12,<13.0a0
+  - cuda-cudart
+  license: BSD-3-Clause
+  license_family: BSD
+  purls: []
+  size: 7841432
+  timestamp: 1779828197486
+- pypi: https://pypi.nvidia.com/ucxx-cu12/ucxx_cu12-0.48.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
+  name: ucxx-cu12
+  version: 0.48.0
+  sha256: 8b8cb638aa416a5a0912e72ca56d2dcf4f7b893771a62f5132d3641e8abedcce
+  requires_dist:
+  - libucxx-cu12==0.48.*
+  - numba-cuda[cu12]>=0.22.1,<0.23.0
+  - numpy>=1.23,<3.0
+  - nvidia-ml-py>=12
+  - rmm-cu12==26.2.*
+  - cloudpickle ; extra == 'test'
+  - cudf-cu12==26.2.* ; extra == 'test'
+  - cupy-cuda12x>=13.6.0 ; extra == 'test'
+  - pytest-asyncio>=1.0.0 ; extra == 'test'
+  - pytest-rerunfailures!=16.0.0 ; extra == 'test'
+  - pytest<9.0.0 ; extra == 'test'
+  - rapids-dask-dependency==26.2.* ; extra == 'test'
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/1b/98/f63318ccbe75c810011fe9233884c5d348d94d90005de1b79e5f93bef9c0/umap_learn-0.5.12-py3-none-any.whl
   name: umap-learn
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@@ -8764,10 +11847,10 @@ packages:
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   - sphinx>=7.1 ; extra == 'dev'
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+- pypi: https://files.pythonhosted.org/packages/40/ee/11225cd4771b0388022d56fcffc8ed5c6bd57029e5a0647377a56a998e04/xarray_spatial-0.10.11-py3-none-any.whl
   name: xarray-spatial
-  version: 0.10.10
-  sha256: e6b12e64dc45fcb70c01ef53a0ddfa79a67de3bc36f3e2c366e083f2d5e39ea9
+  version: 0.10.11
+  sha256: 34a91ea3a0193b4bc429a10fa41aea84c50ce1f87707cdb6f29d9f64b83111bc
   requires_dist:
   - numba
   - scipy
diff --git a/pixi.toml b/pixi.toml
index 3ac819c..6aa9e8e 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -6,12 +6,10 @@ authors = ["Your Name <your.email@example.com>"]
 channels = ["conda-forge"]
 platforms = ["osx-arm64", "linux-64"]
 
-[pypi-options]
-extra-index-urls = ["https://pypi.nvidia.com"]
-
 [tasks]
 lab = "jupyter lab"
 test = "pytest"
+rename = { cmd = "python scripts/rename_package.py", description = "Rename the placeholder package/project (run once on a fresh clone; see scripts/rename_package.py)" }
 install-kernel = "python -m ipykernel install --user --name=analysis-template --display-name='Analysis Template (Pixi)'"
 install-hooks = { cmd = "pre-commit install --install-hooks && nbstripout --install && git config diff.ipynb.textconv 'nbstripout -t'", description = "Install pre-commit hooks + the nbstripout notebook-output filter (run once per clone)" }
 
@@ -28,20 +26,15 @@ slepc4py = "*"
 # Shapely from conda to avoid pygeos build issues
 shapely = "*"
 
-[target.osx-arm64.pypi-dependencies]
-# CPU-only JAX on macOS (MPS handled automatically by torch)
-jax = "<0.9.0"
-
-[target.linux-64.pypi-dependencies]
-# GPU stack for Linux (CUDA 12)
-rapids-singlecell = { version = ">=0.13", extras = ["rapids12"] }
-jax = { version = "<0.9.0", extras = ["cuda12"] }
-
 [pypi-dependencies]
 # Compatibility fix: cuML (rapids dependency) incompatible with sklearn 1.8
 # https://github.com/rapidsai/cuml/issues/6426
 scikit-learn = "<1.8"
 
+# CPU JAX on all platforms by default (MPS handled automatically by torch on
+# macOS). The `gpu` environment overrides this with the CUDA build on Linux.
+jax = "<0.9.0"
+
 # Core single-cell stack
 scanpy = ">=1.10"
 squidpy = "*"
@@ -69,3 +62,21 @@ session-info2 = "*"
 myanalysis = { path = ".", editable = true }
 igraph = ">=1.0.0, <2"
 celltypist = ">=1.7.1, <2"
+
+# GPU stack — only materialized in the `gpu` environment (Linux + CUDA 12).
+# The default environment is CPU-only and is what CI installs; macOS local also
+# uses the default. Activate `gpu` explicitly on a Linux/CUDA box (e.g. Euler):
+#
+#     pixi install -e gpu
+#     pixi run -e gpu install-kernel
+[feature.gpu.pypi-options]
+extra-index-urls = ["https://pypi.nvidia.com"]
+
+[feature.gpu.target.linux-64.pypi-dependencies]
+# `rapids-cu12` extra pulls cuml/cupy/cudf from pypi.nvidia.com; without it
+# rapids-singlecell installs without the GPU libs and silently runs on CPU.
+rapids-singlecell = { version = ">=0.15, <0.16", extras = ["rapids-cu12"] }
+jax = { version = "<0.9.0", extras = ["cuda12"] }
+
+[environments]
+gpu = ["gpu"]
diff --git a/scripts/rename_package.py b/scripts/rename_package.py
new file mode 100644
index 0000000..ab10f46
--- /dev/null
+++ b/scripts/rename_package.py
@@ -0,0 +1,136 @@
+#!/usr/bin/env python3
+"""One-shot renamer for instantiating this template.
+
+Replaces the placeholder package name ``myanalysis`` and the placeholder
+project/kernel name ``analysis-template`` everywhere they appear, and renames
+the ``src/myanalysis`` directory. Run it once, right after cloning your new repo from the template and *before*
+``pixi install`` (it uses only the standard library, so plain ``python`` works):
+
+    python scripts/rename_package.py myproject
+    # or, with an explicit Jupyter display name:
+    python scripts/rename_package.py myproject --display-name "My Project"
+
+(Also available as ``pixi run rename`` once the environment is installed.)
+
+``PACKAGE`` must be a valid Python identifier (letters, digits, underscores;
+not starting with a digit), e.g. ``myproject`` or ``pbmc_atlas``. The project
+slug used for the pixi workspace and the Jupyter kernel is derived from it by
+turning underscores into hyphens (``pbmc_atlas`` -> ``pbmc-atlas``).
+
+The script is intentionally dependency-free (stdlib only) so it runs before the
+environment is installed. It does NOT touch README.md (you're meant to replace
+that with your own project docs) or .env.example.
+"""
+
+from __future__ import annotations
+
+import argparse
+import re
+import sys
+from pathlib import Path
+
+OLD_PACKAGE = "myanalysis"
+OLD_PROJECT = "analysis-template"
+OLD_DISPLAY = "Analysis Template (Pixi)"
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+
+# Files in which to replace the package name (whole-word) and project slug.
+TARGET_FILES = [
+    "pyproject.toml",
+    "pixi.toml",
+    "tests/test_basic.py",
+]
+# Notebooks are scanned dynamically so new ones are picked up too.
+NOTEBOOK_GLOB = "analysis/*.ipynb"
+
+
+def _fail(msg: str) -> None:
+    sys.exit(f"error: {msg}")
+
+
+def replace_in_file(path: Path, replacements: list[tuple[str, str]]) -> bool:
+    """Apply (pattern, repl) regex substitutions to a file. Returns True if changed."""
+    if not path.exists():
+        return False
+    original = path.read_text()
+    text = original
+    for pattern, repl in replacements:
+        text = re.sub(pattern, repl, text)
+    if text != original:
+        path.write_text(text)
+        return True
+    return False
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Rename the template package/project in place.")
+    parser.add_argument("package", help="New package import name (valid Python identifier, e.g. 'myproject').")
+    parser.add_argument(
+        "--display-name",
+        default=None,
+        help="Jupyter kernel display name (default: derived from the package name).",
+    )
+    args = parser.parse_args()
+
+    new_package = args.package
+    if not new_package.isidentifier():
+        _fail(f"{new_package!r} is not a valid Python identifier (use letters, digits, underscores).")
+    if new_package == OLD_PACKAGE:
+        _fail(f"the new name equals the placeholder {OLD_PACKAGE!r}; nothing to do.")
+
+    new_project = new_package.replace("_", "-")
+    new_display = args.display_name or f"{new_package.replace('_', ' ').title()} (Pixi)"
+
+    src_old = REPO_ROOT / "src" / OLD_PACKAGE
+    src_new = REPO_ROOT / "src" / new_package
+    if not src_old.is_dir():
+        _fail(
+            f"{src_old.relative_to(REPO_ROOT)} not found. The template may already be renamed "
+            "(this script is meant to run once on a fresh clone)."
+        )
+    if src_new.exists():
+        _fail(f"{src_new.relative_to(REPO_ROOT)} already exists; refusing to overwrite.")
+
+    # Whole-word replacements so we never touch substrings of other identifiers.
+    replacements = [
+        (rf"\b{re.escape(OLD_PACKAGE)}\b", new_package),
+        (re.escape(OLD_PROJECT), new_project),
+        (re.escape(OLD_DISPLAY), new_display),
+    ]
+
+    changed: list[str] = []
+    for rel in TARGET_FILES:
+        if replace_in_file(REPO_ROOT / rel, replacements):
+            changed.append(rel)
+    # The package's own sources (e.g. `version("myanalysis")` in __init__.py) —
+    # process these before renaming the directory, while the old path is valid.
+    for py in sorted(src_old.rglob("*.py")):
+        if replace_in_file(py, replacements):
+            changed.append(str(py.relative_to(REPO_ROOT)))
+    for nb in sorted(REPO_ROOT.glob(NOTEBOOK_GLOB)):
+        if replace_in_file(nb, replacements):
+            changed.append(str(nb.relative_to(REPO_ROOT)))
+
+    # Rename the package directory last, after its references are updated.
+    src_old.rename(src_new)
+    changed.append(f"src/{OLD_PACKAGE}/ -> src/{new_package}/")
+
+    print(f"Renamed package '{OLD_PACKAGE}' -> '{new_package}'")
+    print(f"Project/kernel slug '{OLD_PROJECT}' -> '{new_project}'")
+    print(f"Kernel display name -> '{new_display}'")
+    print("\nChanged:")
+    for c in changed:
+        print(f"  - {c}")
+    print(
+        "\nNext steps:\n"
+        "  1. Review the diff (git diff / git status).\n"
+        "  2. Update the [workspace] description and authors in pixi.toml.\n"
+        "  3. Replace README.md with your own project docs.\n"
+        "  4. pixi install && pixi run install-hooks && pixi run install-kernel\n"
+        "  5. pixi run test"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/myanalysis/__init__.py b/src/myanalysis/__init__.py
index 9b44508..a336f31 100644
--- a/src/myanalysis/__init__.py
+++ b/src/myanalysis/__init__.py
@@ -1,7 +1,7 @@
 from importlib.metadata import version
 
-from ._constants import FilePaths
+from ._constants import DatasetPaths, FilePaths
 from .plotting import qc_violin
 
-__all__ = ["FilePaths", "qc_violin"]
+__all__ = ["DatasetPaths", "FilePaths", "qc_violin"]
 __version__ = version("myanalysis")
diff --git a/src/myanalysis/_constants.py b/src/myanalysis/_constants.py
index 4eef26c..ac69cd6 100644
--- a/src/myanalysis/_constants.py
+++ b/src/myanalysis/_constants.py
@@ -1,13 +1,77 @@
+"""Project-wide path constants for notebooks and scripts."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
 from pathlib import Path
 
+# Files that mark the repository root, searched for upward from this module.
+_ROOT_MARKERS = ("pixi.toml", ".git")
+
+
+def _find_root(start: Path) -> Path:
+    """Locate the repo root by walking upward until a marker file is found.
+
+    Falls back to the fixed ``src/<package>/`` layout (three levels up) when no
+    marker is present, e.g. for a non-editable installed copy.
+    """
+    for parent in (start, *start.parents):
+        if any((parent / marker).exists() for marker in _ROOT_MARKERS):
+            return parent
+    return start.parents[2]
+
+
+@dataclass(frozen=True)
+class DatasetPaths:
+    """Standard subfolders for a single dataset (``data/<name>/``)."""
+
+    root: Path
+
+    @property
+    def raw(self) -> Path:
+        """Original, unmodified input data."""
+        return self.root / "raw"
+
+    @property
+    def processed(self) -> Path:
+        """Preprocessed / intermediate data."""
+        return self.root / "processed"
+
+    @property
+    def resources(self) -> Path:
+        """Reference data, gene sets, annotations."""
+        return self.root / "resources"
+
+    @property
+    def results(self) -> Path:
+        """Analysis outputs (tables, exported objects)."""
+        return self.root / "results"
+
+    def create(self) -> DatasetPaths:
+        """Create all standard subfolders (idempotent). Returns ``self``."""
+        for path in (self.raw, self.processed, self.resources, self.results):
+            path.mkdir(parents=True, exist_ok=True)
+        return self
+
 
 class FilePaths:
     """Project-wide paths for notebooks and scripts."""
 
-    ROOT = Path(__file__).parents[2].resolve()
+    ROOT = _find_root(Path(__file__).resolve())
 
     DATA = ROOT / "data"
     FIGURES = ROOT / "figures"
 
-    # Example dataset layout; customize per project
+    # The bundled example dataset; customize / add your own via `dataset()`.
     EXAMPLE_DATASET = DATA / "example_dataset"
+
+    @classmethod
+    def dataset(cls, name: str) -> DatasetPaths:
+        """Return the standard raw/processed/resources/results paths for a dataset.
+
+        Examples
+        --------
+        >>> paths = FilePaths.dataset("pbmc3k").create()
+        >>> paths.processed / "adata.h5ad"  # doctest: +SKIP
+        """
+        return DatasetPaths(cls.DATA / name)
diff --git a/src/myanalysis/plotting.py b/src/myanalysis/plotting.py
index 690883d..98f33a9 100644
--- a/src/myanalysis/plotting.py
+++ b/src/myanalysis/plotting.py
@@ -4,9 +4,12 @@
 with project-specific defaults and styling.
 """
 
+from pathlib import Path
+
 import matplotlib.pyplot as plt
 import scanpy as sc
 from anndata import AnnData
+from matplotlib.figure import Figure
 
 
 def qc_violin(
@@ -14,8 +17,8 @@ def qc_violin(
     *,
     groupby: str | None = None,
     figsize: tuple[float, float] = (10, 3),
-    save: str | None = None,
-) -> plt.Figure:
+    save: str | Path | None = None,
+) -> Figure:
     """Plot QC metrics as violin plots with consistent styling.
 
     Parameters
@@ -31,7 +34,8 @@ def qc_violin(
 
     Returns
     -------
-    matplotlib Figure object.
+    Figure
+        The matplotlib figure containing the violin plots.
     """
     qc_vars = ["n_genes_by_counts", "total_counts", "pct_counts_mt"]
     available = [v for v in qc_vars if v in adata.obs.columns]
@@ -48,7 +52,7 @@ def qc_violin(
         sc.pl.violin(adata, var, groupby=groupby, ax=ax, show=False)
         ax.set_title(var.replace("_", " ").title())
 
-    plt.tight_layout()
+    fig.tight_layout()
 
     if save is not None:
         fig.savefig(save, dpi=150, bbox_inches="tight")
diff --git a/tests/test_basic.py b/tests/test_basic.py
index 8d22a5a..d4a4c20 100644
--- a/tests/test_basic.py
+++ b/tests/test_basic.py
@@ -1,31 +1,39 @@
 import anndata as ad
+import matplotlib
 import numpy as np
 import pytest
+from matplotlib.figure import Figure
 
 import myanalysis
 from myanalysis import FilePaths, qc_violin
 
+# Headless backend so plotting works in CI.
+matplotlib.use("Agg")
+
 
 def test_package_has_version():
     assert myanalysis.__version__ is not None
 
 
-def test_filepaths_root_exists():
-    """Verify the project root is correctly resolved."""
-    assert FilePaths.ROOT.exists()
+def test_filepaths():
+    """Project root resolves, and the dataset accessor builds standard subpaths."""
     assert (FilePaths.ROOT / "pixi.toml").exists()
+    ds = FilePaths.dataset("example_dataset")
+    assert ds.raw == FilePaths.DATA / "example_dataset" / "raw"
 
 
-def test_filepaths_directories():
-    """Verify standard directories are defined and accessible."""
-    assert FilePaths.DATA.parent == FilePaths.ROOT
-    assert FilePaths.FIGURES.parent == FilePaths.ROOT
+def test_qc_violin():
+    """qc_violin returns a matplotlib Figure for an AnnData with QC metrics."""
+    rng = np.random.default_rng(0)
+    adata = ad.AnnData(rng.random((20, 5)))
+    for metric in ("n_genes_by_counts", "total_counts", "pct_counts_mt"):
+        adata.obs[metric] = rng.random(20)
 
+    assert isinstance(qc_violin(adata), Figure)
 
-def test_qc_violin_missing_metrics():
-    """Verify qc_violin raises informative error when QC metrics are missing."""
-    # Create minimal AnnData without QC metrics
-    adata = ad.AnnData(np.random.rand(10, 5))
 
+def test_qc_violin_missing_metrics():
+    """qc_violin raises an informative error when QC metrics are missing."""
+    adata = ad.AnnData(np.random.default_rng(0).random((10, 5)))
     with pytest.raises(ValueError, match="No QC metrics found"):
         qc_violin(adata)