Modélisation et approche empirique des réseaux trophiques en Manche-Est et sud mer-du-Nord et un focus sur l'effet du changement climatique sur le développement embryonnaire du hareng des Downs
Bibliographic record
Abstract
Ces travaux scientifiques menés dans le cadre du CPER de la région hauts-de-France MARCO de 2014 à 2021 sur l’écosystème Manche Est par le laboratoire Ressources Halieutiques de l’institut IFREMER à Boulogne sur mer, en collaboration avec d’autres laboratoires de recherche français et étrangers a permis de mieux comprendre cet écosystème à travers les réseaux trophiques (relation proie/prédateur, compétition alimentaires…) avec deux types d’approches très complémentaires : l’une empirique (analyse de données de terrain) et l’autre de modélisation. De plus une étude expérimentale menée en partie à Boulogne sur mer avec le centre de la mer Nausicaa sur le hareng a permis d’identifier les effets potentiels que pouvait entrainer le changement climatique sur les premiers stades de vie de cette espèce commerciale emblématique.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".