DFO Arctic Region Biodiversity of the Benthic Epifauna Trawl Survey from CBS-MEA program (2021-2024)
Bibliographic record
Abstract
This resource documents a dataset of epifauna occurrences collected from 2021 to 2024 during the Canadian Beaufort Sea Marine Ecosystem Assessment (CBS-MEA) conducted by the Department of Fisheries and Oceans (DFO). This scientific program focuses on the integration of oceanography, food web linkages, physical-biological couplings, and spatial and interannual variabilities. The program also aims to expand the baseline coverage of species diversity, abundances, and habitat associations in previously unstudied areas of the Beaufort Sea and Western Canadian Archipelago. Epibenthic invertebrates were identified from catches collected with both a 3 m benthic beam trawl and an Atlantic Western IIA otter trawl. // Cette ressource documente un jeu de données sur les occurrences d'épifaune collectées de 2021 à 2024 lors de l'évaluation environnementale marine de la mer de Beaufort canadienne (CBS-MEA) menée par Pêches et Océans Canada (MPO). Le programme CBS-MEA se concentre sur l'intégration de l'océanographie, des liens dans le réseau alimentaire, des couplages physico-biologiques et des variabilités spatiales et interannuelles. Le programme vise également à élargir la couverture de référence de la diversité des espèces, des abondances et des associations avec les habitats dans des zones de la mer de Beaufort et de l'archipel canadien de l'Ouest précédemment non étudiées. Les invertébrés épibenthiques ont été identifiés à la fois à partir des prises collectées par un chalut à perche benthique de 3 m et aussi par un chalut à panneaux Atlantic Western IIA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".