DFO Quebec Region Biodiversity of the Snow Crab Trawl Survey in Baie Sainte-Marguerite (2006-to-2009, 2023)
Bibliographic record
Abstract
A research survey on snow crab (Chionoecetes opilio) was carried out by DFO from May 2006 to May 2009, and in July 2023, in Baie Sainte-Marguerite near Sept-Îles, Quebec. The main objective of this survey was to assess the abundance of snow crab and species associated with snow crab habitat using a beam trawl. Only data for benthic and demersal species associated with snow crab habitat are presented in this dataset. The data provided is a compilation by species (or taxon), by station. The taxonomic and geographic validity of the records were verified. // Un relevé de recherche sur le crabe des neiges (Chionoecetes opilio) a été réalisé par le MPO de mai 2006 à 2009, ainsi qu'en juillet 2023, dans la Baie Sainte-Marguerite près de Sept-îles, Québec. L’objectif principal de ce relevé était d’évaluer l’abondance du crabe des neiges et des espèces associées à l’habitat du crabe des neiges à l'aide d'un chalut à perche (connu aussi sous le nom de chalut à bâton). Seules les données des espèces benthiques et démersales associées à l’habitat du crabe des neiges sont présentées dans ce jeu de données. Les données fournies sont une compilation par espèce (ou taxon), par station. La validité taxonomique et géographique des enregistrements a été vérifiée.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".