Status of the Anarhichas lupus, A. minor, and A. denticulatus in the Canadian Atlantic and Arctic Regions
Bibliographic record
Abstract
This document provides the latest assessment on the status of Northern Wolffish, Atlantic Wolffish, and Spotted Wolffish stocks that inhabit the Canadian Atlantic and Arctic Regions. There was a noticeable increase in the indices of stock size since the mid–2000s in Newfoundland and Labrador (NL) Region, as well Atlantic Wolffish and Spotted Wolffish in the Quebec Region, but only Spotted Wolffish in Northwest Atlantic Fisheries Organization (NAFO) Divisions (Div.) 2J3K continued to experience some level of recovery in most recent periods, including a northward expansion in range into Div. 2H during the last decade. However, since the last assessment in 2014, population status for all three wolffish species throughout Canadian Atlantic and Arctic waters remains largely unchanged and has shown little recovery. Most wolffish interactions with commercial fisheries occurred in the areas where the stocks are centered, primarily along the slopes of the continental shelf and deep channels, and to a lesser extent over the southern Grand Bank and the remaining portions of the study area. Mobile fleets were responsible for the majority of wolffish removals in NL and Maritimes Regions prior to 2003, as well in the Arctic Region (2000–21), whereas fixed gear fleets accounted for most wolffish removals in the Quebec and Gulf Regions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".