Une version pondérée de la factorisation matricielle non négative pour l'identification de sources de particules atmosphériques. Application au littoral de la mer du Nord
Why this work is in the frame
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Bibliographic record
Abstract
This paper focuses on approximate factorization technics of the measures matrix X(n samples,m sensors) into a contribution matrix G and a profile matrix F. Findin g G and F can be made through specific factorization methods (PMF 1 et NMF 2 ) that look alternatively for the best matrix G and F. In this article, a NMF based algorithm is proposed. It e nables to take advantage of the NMF method on the one hand, and on the other hand to impr ove the accuracy of the results. This algorithm is used on concentration measures of airbor ne particulate coming from the area of Dunkerque coast in periods mainly affected by marine so urces. MOTS-CLES : Pollution de l'Air, Diagnostic, Factorisation matricielle approchee.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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