Hnm4lcp - Un solveur de problèmes de complémentarité linéaire fondé sur l'algorithme de Newton-min hybride
Why this work is in the frame
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Bibliographic record
Abstract
Hnm4lcp is a Matlab code to solve a linear complementarity problem (LCP)of the form (0 ≤ x _|_ (M*x+q) ≥ 0,where x in Rn is the real vector of unknowns, M in Rnxn and q in Rn isthe data. This system means that the sought x must be nonnegativecomponentwise (x ≥ 0), y := M*x+q must be nonnegative componentwise (y ≥0) and x and y must be perpendicular for the Euclidean scalar product(x'*y = 0 or x.*y = 0).It is assumed that M is nondegenerate, meaning that all its principalminors are nonzero (i.e., det(M(I,I)) ~= 0 for all I in [1:n]). There isno verification (this is too expensive) and there is no provision in thecode to deal with a degenerate M. The LCP has a unique solution whateverq is if and only if M is a P-matrix (meaning that its principal minorsare positive: det(M(I,I)) > 0 for all I in [1:n]).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it