Assessment of the West Coast of Newfoundland (NAFO Division 4R) Atlantic Herring (Clupea harengus) stocks in 2021
Bibliographic record
Abstract
This document details the data and analyses used to assess the status of the west coast of Newfoundland (NAFO Division 4R) spring- and fall-spawning herring stocks. The present stock assessment took place on March 1-2, 2022 and provides advice for the 2022-2023 fishing seasons. The data and knowledge available are insufficient to quantitatively assess the status of the resource. However, the main results of this assessment indicate that maintaining the TAC at status quo should not pose any significant risk to the two herring spawning stocks in Division 4R in the short term. Maximum exploitation rates in 2020-2021, estimated as the ratio of the TAC over the highest biomass index estimated in the acoustic survey, were low (<15%). The abundance of young fish observed in the 2020-2021 acoustic surveys and commercial catches for both spring and fall spawners is an encouraging sign for the future of these stocks. Landings have been trending downward since 2017, and the recent decrease of 81% since 2019 can be explained by the high incidence of fish under the legal size that prevented harvesters from landing their quotas. After a period of low stock status in the 2000s and 2010s, there are signs of increase for the spring-spawning stock since 2019. This conclusion will need to be reconsidered following the review of the assessment framework in 2024-2025.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".