Guide salle tri Thalassa 2019. Campagnes halieutiques
Bibliographic record
Abstract
Ce document présente, pour les novices mais aussi pour les « habitués », le fonctionnement global de la salle de tri de la Thalassa, lors des campagnes halieutiques. Il permettra de se familiariser avec cet outil avant l’embarquement, sachant que la formation sera progressivement affinée et complétée à bord. Suite à la modernisation de la Thalassa en 2017, la salle de tri a en effet subi un nombre conséquent de modifications et notamment l’informatisation des postes de travail. Même si le travail de base demeure le même, il convient de prendre et de respecter quelques précautions d’usage, afin de limiter les erreurs et de fournir des données de qualité. Ce document tentera de fournir les premières bases (ou vous permettre de vous remémorer certains points) et aura une vocation de support aux conseils des personnes les plus expérimentées.\n
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.189 | 0.132 |
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".