diff --git a/docs/source/api/developer.rst b/docs/source/api/developer.rst
index 2d14753a3..8b013ec55 100644
--- a/docs/source/api/developer.rst
+++ b/docs/source/api/developer.rst
@@ -10,7 +10,6 @@ OTT Backend
 
     moscot.backends.ott.SinkhornSolver
     moscot.backends.ott.GWSolver
-    moscot.backends.ott.FGWSolver
     moscot.backends.ott.OTTOutput
     moscot.backends.ott.OTTCost
 
diff --git a/docs/source/api/user.rst b/docs/source/api/user.rst
index c7e674cf4..8924defcc 100644
--- a/docs/source/api/user.rst
+++ b/docs/source/api/user.rst
@@ -28,4 +28,3 @@ Generic Problems
 
     SinkhornProblem
     GWProblem
-    FGWProblem
diff --git a/docs/source/conf.py b/docs/source/conf.py
index c3b329f5e..085c221be 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -49,6 +49,7 @@
     "sphinx.ext.autodoc",
     "sphinx.ext.napoleon",
     "sphinx.ext.viewcode",
+    "sphinx.ext.mathjax",
     "sphinx_autodoc_typehints",
     "sphinx.ext.intersphinx",
     "sphinx.ext.autosummary",
diff --git a/docs/source/extensions/typed_returns.py b/docs/source/extensions/typed_returns.py
index a18e9933f..d5126910f 100644
--- a/docs/source/extensions/typed_returns.py
+++ b/docs/source/extensions/typed_returns.py
@@ -10,7 +10,10 @@ def process_return(lines: Iterable[str]) -> Iterator[str]:
         m = re.fullmatch(r"(?P<param>\w+)\s+:\s+(?P<type>[\w.]+)", line)
         if m:
             # Once this is in scanpydoc, we can use the fancy hover stuff
-            yield f'**{m["param"]}** : :class:`~{m["type"]}`'
+            if m["param"]:
+                yield f'**{m["param"]}** : :class:`~{m["type"]}`'
+            else:
+                yield f':class:`~{m["type"]}`'
         else:
             yield line
 
diff --git a/src/moscot/_docs/_docs.py b/src/moscot/_docs/_docs.py
index 29727d604..a4ffa25e5 100644
--- a/src/moscot/_docs/_docs.py
+++ b/src/moscot/_docs/_docs.py
@@ -85,7 +85,7 @@
 data
     - If `data` is a :class:`str` this should correspond to a column in :attr:`anndata.AnnData.obs`.
       The transport map is applied to the subset corresponding to the source distribution
-      (if `forward` is `True`) or target distribution (if `forward` is `False`) of that column.
+      (if `forward` is `True`) or target distribution (if `forward` is :obj:`False`) of that column.
     - If `data` is a :class:npt.ArrayLike the transport map is applied to `data`.
     - If `data` is a :class:`dict` then the keys should correspond to the tuple defining a single optimal
       transport map and the value should be one of the two cases described above.
@@ -94,18 +94,20 @@
 subset
     Subset of :attr:`anndata.AnnData.obs` ``['{key}']`` values of which the policy is to be applied to.
 """
-_marginal_kwargs = """\
+_marginal_kwargs = r"""
 marginal_kwargs
-    keyword arguments for :meth:`moscot.problems.BirthDeathProblem._estimate_marginals`, i.e.
-    for modeling the birth-death process. The keyword arguments
-    are either used for :func:`moscot.problems.time._utils.beta`, i.e. one of:
+    Keyword arguments for :meth:`~moscot.problems.BirthDeathProblem._estimate_marginals`. If ``'scaling'``
+    is in ``marginal_kwargs``, the left marginals are computed as
+    :math:`\exp(\frac{(\textit{proliferation} - \textit{apoptosis}) \cdot (t_2 - t_1)}{\textit{scaling}})`.
+    Otherwise, the left marginals are computed using a birth-death process. The keyword arguments
+    are either used for :func:`~moscot.problems.time._utils.beta`, i.e. one of:
 
         - beta_max: float
         - beta_min: float
         - beta_center: float
         - beta_width: float
 
-    or for :func:`moscot.problems.time._utils.beta`, i.e. one of:
+    or for :func:`~moscot.problems.time._utils.delta`, i.e. one of:
 
         - delta_max: float
         - delta_min: float
@@ -127,13 +129,35 @@
 _a = """\
 a
     Specifies the left marginals. If of type :class:`str` the left marginals are taken from
-    :attr:`anndata.AnnData.obs` ``['{a}']``. If `a` is `None` uniform marginals are used.
+    :attr:`anndata.AnnData.obs` ``['{a}']``. If ``a`` is `None` uniform marginals are used.
 """
 _b = """\
 b
     Specifies the right marginals. If of type :class:`str` the right marginals are taken from
     :attr:`anndata.AnnData.obs` ``['{b}']``. If `b` is `None` uniform marginals are used.
 """
+_a_temporal = r"""
+a
+    Specifies the left marginals. If
+        - ``a`` is :class:`str` - the left marginals are taken from :attr:`anndata.AnnData.obs`,
+        - if :meth:`~moscot.problems.base._birth_death.BirthDeathMixin.score_genes_for_marginals` was run and
+          if ``a`` is `None`, marginals are computed based on a birth-death process as suggested in
+          :cite:`schiebinger:19`,
+        - if :meth:`~moscot.problems.base._birth_death.BirthDeathMixin.score_genes_for_marginals` was run and
+          if ``a`` is `None`, and additionally ``'scaling'`` is provided in ``marginal_kwargs``,
+          the marginals are computed as
+          :math:`\exp(\frac{(\textit{proliferation} - \textit{apoptosis}) \cdot (t_2 - t_1)}{\textit{scaling}})`
+          rather than using a birth-death process,
+        - otherwise or if ``a`` is :obj:`False`, uniform marginals are used.
+"""
+_b_temporal = """\
+b
+    Specifies the right marginals. If
+        - ``b`` is :class:`str` - the left marginals are taken from :attr:`anndata.AnnData.obs`,
+        - if :meth:`~moscot.problems.base._birth_death.BirthDeathMixin.score_genes_for_marginals` was run
+          uniform (mean of left marginals) right marginals are used,
+        - otherwise or if ``b`` is :obj:`False`, uniform marginals are used.
+"""
 _time_key = """\
 time_key
     Time point key in :attr:`anndata.AnnData.obs`.
@@ -400,6 +424,8 @@
     converged=_converged,
     a=_a,
     b=_b,
+    a_temporal=_a_temporal,
+    b_temporal=_b_temporal,
     time_key=_time_key,
     spatial_key=_spatial_key,
     batch_key=_batch_key,
diff --git a/src/moscot/_docs/_docs_mixins.py b/src/moscot/_docs/_docs_mixins.py
index 3af941609..89e5b1f14 100644
--- a/src/moscot/_docs/_docs_mixins.py
+++ b/src/moscot/_docs/_docs_mixins.py
@@ -55,10 +55,7 @@
     for the corresponding plotting functions are stored.
     See TODO Notebook for how :mod:`moscot.plotting` works.
 """
-_return_cell_transition = """\
-retun_cell_transition
-    Transition matrix of cells or groups of cells.
-"""
+_return_cell_transition = "Transition matrix of cells or groups of cells."
 _notes_cell_transition = """\
 To visualise the results, see :func:`moscot.pl.cell_transition`.
 """
diff --git a/src/moscot/problems/base/_birth_death.py b/src/moscot/problems/base/_birth_death.py
index fbfb8db05..96c00a64b 100644
--- a/src/moscot/problems/base/_birth_death.py
+++ b/src/moscot/problems/base/_birth_death.py
@@ -1,4 +1,5 @@
-from typing import Any, Union, Literal, Callable, Optional, Protocol, Sequence, TYPE_CHECKING
+from types import MappingProxyType
+from typing import Any, Union, Literal, Mapping, Callable, Optional, Protocol, Sequence, TYPE_CHECKING
 
 import numpy as np
 
@@ -68,7 +69,7 @@ def score_genes_for_marginals(
         to proliferation and/or apoptosis must be passed.
 
         Alternatively, proliferation and apoptosis genes for humans and mice are saved in :mod:`moscot`.
-        The gene scores will be used in :meth:`moscot.problems.TemporalProblem.prepare` to estimate the initial
+        The gene scores will be used in :meth:`~moscot.problems.CompoundBaseProblem.prepare` to estimate the initial
         growth rates as suggested in :cite:`schiebinger:19`
 
         Parameters
@@ -175,9 +176,10 @@ def _estimate_marginals(
         source: bool,
         proliferation_key: Optional[str] = None,
         apoptosis_key: Optional[str] = None,
-        **kwargs: Any,
+        marginal_kwargs: Mapping[str, Any] = MappingProxyType({}),
+        **_: Any,
     ) -> ArrayLike:
-        def estimate(key: Optional[str], *, fn: Callable[..., ArrayLike]) -> ArrayLike:
+        def estimate(key: Optional[str], *, fn: Callable[..., ArrayLike], **kwargs: Any) -> ArrayLike:
             if key is None:
                 return np.zeros(adata.n_obs, dtype=float)
             try:
@@ -189,16 +191,22 @@ def estimate(key: Optional[str], *, fn: Callable[..., ArrayLike]) -> ArrayLike:
             raise ValueError("Either `proliferation_key` or `apoptosis_key` must be specified.")
         self.proliferation_key = proliferation_key
         self.apoptosis_key = apoptosis_key
+        if "scaling" in marginal_kwargs:
+            beta_fn = delta_fn = lambda x, *args, **kwargs: x
+            scaling = marginal_kwargs["scaling"]
+        else:
+            beta_fn, delta_fn = beta, delta
+            scaling = 1
+        birth = estimate(proliferation_key, fn=beta_fn, **marginal_kwargs)
+        death = estimate(apoptosis_key, fn=delta_fn, **marginal_kwargs)
+
+        prior_growth = np.exp((birth - death) * self.delta / scaling)
 
-        birth = estimate(proliferation_key, fn=beta)
-        death = estimate(apoptosis_key, fn=delta)
-        prior_growth = np.exp((birth - death) * self.delta)
         scaling = np.sum(prior_growth)
         normalized_growth = prior_growth / scaling
         if source:
             self._scaling = scaling
             self._prior_growth = prior_growth
-
         return normalized_growth if source else np.full(self.adata_tgt.n_obs, fill_value=np.mean(normalized_growth))
 
     # TODO(michalk8): temporary fix to satisfy the mixin, consider removing the mixin
diff --git a/src/moscot/problems/base/_compound_problem.py b/src/moscot/problems/base/_compound_problem.py
index 5b11a53e6..3d24b1c62 100644
--- a/src/moscot/problems/base/_compound_problem.py
+++ b/src/moscot/problems/base/_compound_problem.py
@@ -351,7 +351,7 @@ def _(
         return res if return_all else current_mass
 
     @d.get_sections(base="BaseCompoundProblem_push", sections=["Parameters", "Raises"])
-    @d.dedent
+    @d.dedent  # TODO(@MUCDK) document private _apply
     def push(self, *args: Any, **kwargs: Any) -> ApplyOutput_t[K]:
         """
         Push mass from `start` to `end`.
@@ -371,7 +371,7 @@ def push(self, *args: Any, **kwargs: Any) -> ApplyOutput_t[K]:
         %(scale_by_marginals)s
 
         kwargs
-            keyword arguments for :meth:`moscot.problems.CompoundProblem._apply`.
+            keyword arguments for policy-specific `_apply` method of :class:`moscot.problems.CompoundProblem`.
 
         Returns
         -------
@@ -382,7 +382,7 @@ def push(self, *args: Any, **kwargs: Any) -> ApplyOutput_t[K]:
         return self._apply(*args, forward=True, **kwargs)
 
     @d.get_sections(base="BaseCompoundProblem_pull", sections=["Parameters", "Raises"])
-    @d.dedent
+    @d.dedent  # TODO(@MUCDK) document private functions
     def pull(self, *args: Any, **kwargs: Any) -> ApplyOutput_t[K]:
         """
         Pull mass from `end` to `start`.
@@ -402,7 +402,7 @@ def pull(self, *args: Any, **kwargs: Any) -> ApplyOutput_t[K]:
         %(scale_by_marginals)s
 
         kwargs
-            Keyword arguments for :meth:`moscot.problems.CompoundProblem._apply`.
+            keyword arguments for policy-specific `_apply` method of :class:`moscot.problems.CompoundProblem`.
 
         Returns
         -------
diff --git a/src/moscot/problems/time/_lineage.py b/src/moscot/problems/time/_lineage.py
index a75fba7fe..c0736eabb 100644
--- a/src/moscot/problems/time/_lineage.py
+++ b/src/moscot/problems/time/_lineage.py
@@ -48,6 +48,7 @@ def prepare(
         cost: Literal["sq_euclidean", "cosine", "bures", "unbalanced_bures"] = "sq_euclidean",
         a: Optional[str] = None,
         b: Optional[str] = None,
+        marginal_kwargs: Mapping[str, Any] = MappingProxyType({}),
         **kwargs: Any,
     ) -> "TemporalProblem":
         """
@@ -61,8 +62,9 @@ def prepare(
         %(joint_attr)s
         %(policy)s
         %(cost_lin)s
-        %(a)s
-        %(b)s
+        %(a_temporal)s
+        %(b_temporal)s
+        %(marginal_kwargs)s
         %(kwargs_prepare)s
 
 
@@ -84,7 +86,7 @@ def prepare(
         xy, x, y = handle_cost(xy=xy, x=kwargs.pop("x", None), y=kwargs.pop("y", None), cost=cost)
 
         # TODO(michalk8): needs to be modified
-        marginal_kwargs = dict(kwargs.pop("marginal_kwargs", {}))
+        marginal_kwargs = dict(marginal_kwargs)
         marginal_kwargs["proliferation_key"] = self.proliferation_key
         marginal_kwargs["apoptosis_key"] = self.apoptosis_key
         if a is None:
@@ -316,6 +318,7 @@ def prepare(
         ] = "sq_euclidean",
         a: Optional[str] = None,
         b: Optional[str] = None,
+        marginal_kwargs: Mapping[str, Any] = MappingProxyType({}),
         **kwargs: Any,
     ) -> "LineageProblem":
         """
@@ -331,8 +334,9 @@ def prepare(
         %(joint_attr)s
         %(policy)s
         %(cost)s
-        %(a)s
-        %(b)s
+        %(a_temporal)s
+        %(b_temporal)s
+        %(marginal_kwargs)s
         %(kwargs_prepare)s
 
         Returns
@@ -364,6 +368,7 @@ def prepare(
             cost=cost,
             a=a,
             b=b,
+            marginal_kwargs=marginal_kwargs,
             **kwargs,
         )
 
diff --git a/src/moscot/problems/time/_mixins.py b/src/moscot/problems/time/_mixins.py
index 12a11e118..39f71d47e 100644
--- a/src/moscot/problems/time/_mixins.py
+++ b/src/moscot/problems/time/_mixins.py
@@ -2,6 +2,7 @@
 from pathlib import Path
 import itertools
 
+from pandas.api.types import infer_dtype, is_numeric_dtype
 import pandas as pd
 
 import numpy as np
@@ -459,6 +460,7 @@ def _get_data(
             target_data,
         )
 
+    @d_mixins.dedent
     def compute_interpolated_distance(
         self: TemporalMixinProtocol[K, B],
         source: K,
@@ -502,7 +504,7 @@ def compute_interpolated_distance(
         %(use_posterior_marginals)s
         %(seed_sampling)s
         %(backend)s
-        %(kwargs_divergence)
+        %(kwargs_divergence)s
 
         Returns
         -------
@@ -534,6 +536,7 @@ def compute_interpolated_distance(
             point_cloud_1=intermediate_data, point_cloud_2=interpolation, backend=backend, **kwargs
         )
 
+    @d_mixins.dedent
     def compute_random_distance(
         self: TemporalMixinProtocol[K, B],
         source: K,
@@ -544,7 +547,7 @@ def compute_random_distance(
         account_for_unbalancedness: bool = False,
         posterior_marginals: bool = True,
         seed: Optional[int] = None,
-        backend: Literal["ott"] = "ott",
+        backend: Literal["ott"] = "ott",  # TODO: not used
         **kwargs: Any,
     ) -> Numeric_t:
         """
@@ -566,7 +569,7 @@ def compute_random_distance(
         %(use_posterior_marginals)s
         %(seed_interpolation)s
         %(backend)s
-        %(kwargs_divergence)
+        %(kwargs_divergence)s
 
         Returns
         -------
@@ -592,6 +595,7 @@ def compute_random_distance(
         )
         return self._compute_wasserstein_distance(intermediate_data, random_interpolation, **kwargs)
 
+    @d_mixins.dedent
     def compute_time_point_distances(
         self: TemporalMixinProtocol[K, B],
         source: K,
@@ -770,6 +774,11 @@ def temporal_key(self) -> Optional[str]:
     def temporal_key(self: TemporalMixinProtocol[K, B], key: Optional[str]) -> None:
         if key is not None and key not in self.adata.obs:
             raise KeyError(f"Unable to find temporal key in `adata.obs[{key!r}]`.")
+        if key is not None and not is_numeric_dtype(self.adata.obs[key]):
+            raise TypeError(
+                "Temporal key has to be of numeric type."
+                f"Found `adata.obs[{key!r}]` to be of type `{infer_dtype(self.adata.obs[key])}`."
+            )
         self._temporal_key = key
 
 
diff --git a/src/moscot/problems/time/_utils.py b/src/moscot/problems/time/_utils.py
index 8e2679da9..44553023e 100644
--- a/src/moscot/problems/time/_utils.py
+++ b/src/moscot/problems/time/_utils.py
@@ -11,30 +11,30 @@ def logistic(x: ArrayLike, L: float, k: float, center: float = 0) -> ArrayLike:
     return L / (1 + np.exp(-k * (x - center)))
 
 
-def gen_logistic(p: ArrayLike, beta_max: float, beta_min: float, center: float, width: float) -> ArrayLike:
+def gen_logistic(p: ArrayLike, sup: float, inf: float, center: float, width: float) -> ArrayLike:
     """Shifted logistic function."""
-    return beta_min + logistic(p, L=beta_max - beta_min, k=4 / width, center=center)
+    return inf + logistic(p, L=sup - inf, k=4 / width, center=center)
 
 
 def beta(
     p: ArrayLike,
     beta_max: float = 1.7,
     beta_min: float = 0.3,
-    center: float = 0.25,
-    width: float = 0.5,
+    beta_center: float = 0.25,
+    beta_width: float = 0.5,
     **_: Any,
 ) -> ArrayLike:
     """Birth process."""
-    return gen_logistic(p, beta_max, beta_min, center, width)
+    return gen_logistic(p, beta_max, beta_min, beta_center, beta_width)
 
 
 def delta(
     a: ArrayLike,
     delta_max: float = 1.7,
     delta_min: float = 0.3,
-    center: float = 0.1,
-    width: float = 0.2,
-    **kwargs: Any,
+    delta_center: float = 0.1,
+    delta_width: float = 0.2,
+    **_: Any,
 ) -> ArrayLike:
     """Death process."""
-    return gen_logistic(a, delta_max, delta_min, center, width)
+    return gen_logistic(a, delta_max, delta_min, delta_center, delta_width)
diff --git a/tests/problems/time/test_mixins.py b/tests/problems/time/test_mixins.py
index 8418a9b52..b6b76a711 100644
--- a/tests/problems/time/test_mixins.py
+++ b/tests/problems/time/test_mixins.py
@@ -332,3 +332,16 @@ def test_cell_transition_regression_notparam(
         res = result.sort_index().sort_index(1)
         df_expected = adata_time_with_tmap.uns["cell_transition_gt"].sort_index().sort_index(1)
         np.testing.assert_almost_equal(res.values, df_expected.values, decimal=8)
+
+    @pytest.mark.fast()
+    @pytest.mark.parametrize("temporal_key", ["celltype", "time", "missing"])
+    def test_temporal_key_numeric(self, adata_time: AnnData, temporal_key: str):
+        problem = TemporalProblem(adata_time)
+        if temporal_key == "missing":
+            with pytest.raises(KeyError, match="Unable to find temporal key"):
+                problem = problem.prepare(temporal_key)
+        elif temporal_key == "celltype":
+            with pytest.raises(TypeError, match="Temporal key has to be of numeric type"):
+                problem = problem.prepare(temporal_key)
+        elif temporal_key == "time":
+            problem = problem.prepare(temporal_key)
diff --git a/tests/problems/time/test_temporal_base_problem.py b/tests/problems/time/test_temporal_base_problem.py
index 47270f8ad..38b876005 100644
--- a/tests/problems/time/test_temporal_base_problem.py
+++ b/tests/problems/time/test_temporal_base_problem.py
@@ -1,4 +1,4 @@
-from typing import List, Optional
+from typing import Any, List, Mapping, Optional
 
 import pytest
 
@@ -95,3 +95,38 @@ def test_posterior_growth_rates(self, adata_time_marginal_estimations: AnnData):
 
         gr = prob.posterior_growth_rates
         assert isinstance(gr, np.ndarray)
+
+    @pytest.mark.fast()
+    @pytest.mark.parametrize(
+        "marginal_kwargs", [{}, {"delta_width": 0.9}, {"delta_center": 0.9}, {"beta_width": 0.9}, {"beta_center": 0.9}]
+    )
+    def test_marginal_kwargs(self, adata_time_marginal_estimations: AnnData, marginal_kwargs: Mapping[str, Any]):
+        t1, t2 = 0, 1
+        adata_x = adata_time_marginal_estimations[adata_time_marginal_estimations.obs["time"] == t1]
+        adata_y = adata_time_marginal_estimations[adata_time_marginal_estimations.obs["time"] == t2]
+
+        prob = BirthDeathProblem(adata_x, adata_y, src_key=t1, tgt_key=t2)
+        prob = prob.prepare(
+            x={"attr": "X"},
+            y={"attr": "X"},
+            a=True,
+            b=True,
+            proliferation_key="proliferation",
+            apoptosis_key="apoptosis",
+        )
+
+        gr1 = prob.prior_growth_rates
+        prob = prob.prepare(
+            x={"attr": "X"},
+            y={"attr": "X"},
+            a=True,
+            b=True,
+            proliferation_key="proliferation",
+            apoptosis_key="apoptosis",
+            marginal_kwargs=marginal_kwargs,
+        )
+        gr2 = prob.prior_growth_rates
+        if len(marginal_kwargs) > 0:
+            assert not np.allclose(gr1, gr2)
+        else:
+            assert np.allclose(gr1, gr2)
diff --git a/tests/problems/time/test_temporal_problem.py b/tests/problems/time/test_temporal_problem.py
index 82c9c5ab5..4d0aa22b5 100644
--- a/tests/problems/time/test_temporal_problem.py
+++ b/tests/problems/time/test_temporal_problem.py
@@ -7,6 +7,7 @@
 
 from anndata import AnnData
 
+from tests._utils import ATOL, RTOL
 from moscot.problems.time import TemporalProblem
 from moscot.solvers._output import BaseSolverOutput
 from tests.problems.conftest import (
@@ -135,6 +136,24 @@ def test_apoptosis_key_pipeline(self, adata_time: AnnData):
         problem.apoptosis_key = "new_apoptosis"
         assert problem.apoptosis_key == "new_apoptosis"
 
+    @pytest.mark.fast()
+    @pytest.mark.parametrize("scaling", [0.1, 1, 4])
+    def test_proliferation_key_c_pipeline(self, adata_time: AnnData, scaling: float):
+        keys = np.sort(np.unique(adata_time.obs["time"].values))
+        adata_time = adata_time[adata_time.obs["time"].isin([keys[0], keys[1]])]
+        delta = keys[1] - keys[0]
+        problem = TemporalProblem(adata_time)
+        assert problem.proliferation_key is None
+
+        problem.score_genes_for_marginals(gene_set_proliferation="human", gene_set_apoptosis="human")
+        assert problem.proliferation_key == "proliferation"
+
+        problem = problem.prepare(time_key="time", marginal_kwargs={"scaling": scaling})
+        prolif = adata_time[adata_time.obs["time"] == keys[0]].obs["proliferation"]
+        apopt = adata_time[adata_time.obs["time"] == keys[0]].obs["apoptosis"]
+        expected_marginals = np.exp((prolif - apopt) * delta / scaling)
+        np.testing.assert_allclose(problem[keys[0], keys[1]]._prior_growth, expected_marginals, rtol=RTOL, atol=ATOL)
+
     def test_cell_costs_source_pipeline(self, adata_time: AnnData):
         problem = TemporalProblem(adata=adata_time)
         problem = problem.prepare("time")
diff --git a/tox.ini b/tox.ini
index fb8d61247..1040311e3 100644
--- a/tox.ini
+++ b/tox.ini
@@ -113,26 +113,23 @@ commands =
 
 [testenv:lint]
 description = Perform linting.
-basepython = python3.9
 deps = pre-commit>=2.14.0
 skip_install = true
 commands = pre-commit run --all-files --show-diff-on-failure {posargs:}
 
 [testenv:clean-docs]
 description = Clean the documentation artifacts.
-basepython = python3.8
 deps =
 skip_install = true
 changedir = {toxinidir}/docs
-whitelist_externals = make
+allowlist_externals = make
 commands = make clean
 
 [testenv:docs]
 description = Build the documentation.
-basepython = python3.9
 skip_install = false
 extras = docs
-whitelist_externals = sphinx-build
+allowlist_externals = sphinx-build
 commands =
-    sphinx-build --color -b html {toxinidir}/docs/source {toxinidir}/docs/build/html
+    sphinx-build --color -b html {toxinidir}/docs/source {toxinidir}/docs/build/html {posargs}
     python -c 'import pathlib; print(f"Documentation is available under:", pathlib.Path(f"{toxinidir}") / "docs" / "build" / "html" / "index.html")'