LINEAR_LAG_MODEL
================

Python object: ``phenotypic.schema._linear_lag_model.LINEAR_LAG_MODEL``

Fitted parameters of the linear-softplus lag model (no saturation).

Output columns are **metric-qualified**: each header is
``LinearLagModel_<metric>_<parameter>``, where ``<metric>`` records the
measurement the model was fit on (``self.on`` with its category prefix
stripped, e.g. ``Shape_Area`` → ``Area``). For example, fitting on
``Shape_Area`` emits ``LinearLagModel_Area_v`` (post-lag growth rate) and
``LinearLagModel_Area_s0`` (initial size). The labels below are the
``<parameter>`` segment; the ``<metric>`` infix is filled in at fit time.

.. list-table:: Category: **LinearLagModel**
   :header-rows: 1

   * - Column label
     - Description
     - Type
     - Biology
   * - ``LinearLagModel_v``
     - The post-lag phase growth rate.
     - :bdg-ref-success:`Tier 1 · Direct phenotype <measurement-tiers>`
     - The post-lag phase growth rate using the target metric (usually radius)
   * - ``LinearLagModel_s0``
     - The initial value of the target metric
     - :bdg-ref-success:`Tier 1 · Direct phenotype <measurement-tiers>`
     - The initial size
   * - ``LinearLagModel_lambda``
     - The duration of the lag phase
     - :bdg-ref-success:`Tier 1 · Direct phenotype <measurement-tiers>`
     - 
   * - ``LinearLagModel_alpha``
     - lag phase transition sharpness
     - :bdg-ref-primary:`Tier 2 · Descriptive trait <measurement-tiers>`
     -