Bibliographic record
Abstract
This special issue is dedicated to the autumn school ASEM23 devoted to Equilibrium Problems and Minimax Inequalities, which was held during September 25-26, 2023 in El Jadida, Morocco, and the autumn school ASSVAS23 on Set-valued and Variational Analysis: Applications to physics and economy organized in Safi, Morocco, on two sessions: September 28-29 and November 15-16, 2023.These events are the fruit of a deep cooperation between the laboratory of fundamental mathematics and applications of El Jadida and the former Laboratory of fundamental and applied physics of Safi (LPFAS) whose name is changed now into: Laboratory of Physics, Energies, Environments and Their Applications (LP2EA).A warm acknowledgment goes to the members of these structures for their deep involvement in the organization of our workshops, especially Prof. Ahmed Serhir from LMFA laboratory, the director of LPFAS laboratory Prof. Saida bahsine, the deputy director of LPFAS Prof. Ahmed Daassou and the director of LP2EA Prof. Rachid Benbrik.It is our immense pleasure to acknowledge here the support of our partners: Chouaïb Doukkali
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.479 | 0.313 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".