La grande baie Saint-Nicolas - Caractérisation des habitats littoraux d'importance de la rive nord de l'estuaire maritime du Saint Laurent
Bibliographic record
Abstract
Un projet de caractérisation des habitats littoraux d’importance de la rive nord de l’estuaire maritime du Saint-Laurent a été subventionné pour une période de 4 ans (2023-2027). Ce projet a pour but de générer des données écologiques de référence pour tracer un portrait global de l’état des habitats littoraux le long de la rive nord de l'estuaire maritime. Ce jeu de données couvre le secteur de la grande baie Saint-Nicolas (municipalité de Franquelin). Afin d'améliorer les connaissances de cet écosystème, des inventaires floristiques et fauniques (ichtyologiques) ont été réalisés et les différents facteurs abiotiques caractérisés. Ce projet fait partie du Programme sur les données environnementales côtières de référence de Pêche et Océans Canada.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".