Évaluation du potentiel de rétablissement de la grosse poule de mer (Cyclopterus lumpus) dans les océans Atlantique et Arctique
Bibliographic record
Abstract
Common Lumpfish (Cyclopterus lumpus) in Atlantic Canada was designated as Threatened by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) in 2017, due to severe declines in both research survey abundance and biomass indices and commercial landings. In support of listing recommendations by the Minister, Fisheries and Oceans Canada has been asked to undertake a Recovery Potential Assessment (RPA) for Common Lumpfish, based on the national RPA Guidance. A review of available data indicates that survey indices remain low in areas historically associated with higher Common Lumpfish abundance and biomass (i.e., Subdivision [Subdiv.] 3Ps; Division [Div.] 3KL). In addition, commercial landings remain low. Attempts to model Common Lumpfish in this Designatable Unit (DU) using survey and fishery data were unsuccessful. Therefore, precautionary management is advised based on survey-based proxy reference points. Since commercial fishing is the only quantified source of anthropogenic mortality, and the directed fishery targets the eggs of mature females, a reduction in fishing mortality may be required to achieve recovery targets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".