Improve phenotype scaling and safeguarded line search

README.md

@@ -17,6 +17,11 @@ The engine diagonalizes the GRM once, rotates the common design and every unique
 - C++17 numerical core using oneMKL or OpenBLAS/LAPACKE.
 - GRM eigendecomposition once per task set.
 - AI-REML with a strong-Wolfe line search; no EM updates.
+- Per-task OLS-residual phenotype scaling inside the numerical core, with all
+  estimates and the restricted likelihood restored to the input phenotype units.
+- Safeguarded quadratic zoom interpolation (central 96% of the bracket),
+  bisection fallback, and a last-valid-improving-point fallback when strict Wolfe
+  curvature cannot be reached because of numerical roundoff.
 - Signed standard-deviation parameterization with a separate one-sided KKT check for the \(\sigma_g^2=0\) boundary.
 - No explicit dense \(P\) matrix.
 - Variable numbers of extra fixed-effect covariates per task through a CSR index.
@@ -25,6 +30,13 @@ The engine diagonalizes the GRM once, rotates the common design and every unique
 
 The numerical core has no knowledge of cohorts, molecular assay types, or domain-specific variable names.
 
+The line search starts at 1, expands by 1.618 up to the configured maximum
+step, and uses quadratic interpolation only when its stationary point lies at
+least 2% away from both bracket endpoints. An invalid interpolation falls back
+to bisection. If the evaluation limit is reached, the search accepts the last
+finite covariance-valid point that improved the likelihood; it reports
+`line_search_failed` only when no such point exists.
+
 ## Repository layout
 
 ```text