Improve phenotype scaling and safeguarded line search
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@@ -150,6 +150,17 @@ numerical_error
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`converged_boundary` is a successful residual-only solution accepted after the one-sided variance-component score and likelihood checks.
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Phenotypes are scaled internally by their task-specific OLS residual RMS before
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optimization. Reported fixed effects, fixed-effect covariance, variance
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components, and restricted likelihood are transformed back to the original
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input phenotype units. Input binary files are never modified.
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The strong-Wolfe zoom uses safeguarded quadratic interpolation with a 2%
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endpoint margin and falls back to bisection. At an evaluation limit or a
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collapsed bracket, the last valid likelihood-improving point encountered is
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accepted. `line_search_failed` therefore means that the search found no valid
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point that improved the starting likelihood.
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## Generic finalized output
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The Python CLI exports one TSV row per task. It includes the full summary plus:
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