Science Response : Northern shrimp in the Estuary and Gulf of St. Lawrence
Bibliographic record
Abstract
The review of the Precautionary Approach (PA) of northern shrimp (Pandalus borealis) stocks in the Estuary and Gulf of St. Lawrence (EGSL) began in 2020-2021. A working group, made up of representatives from Fisheries and Oceans Canada (DFO, Science and Fisheries Management [FM] sectors), industry, provincial governments of Quebec and the Atlantic provinces as well as indigenous groups, was created in spring 2021 to develop a PA proposal. This proposal was to include limit, upper and target reference points (LRP, USR and TRP), as well as scenarios of harvest control rules (HCR). In parallel, a review of stock assessment units and a new assessment model were completed on June 28, 2023 during a Canadian Science Advisory Secretariat (CSAS) meeting held in Mont-Joli (Smith and Bourdages 2023, In press, Bourdages et al. 2023). The development of the present PA is based on this work. The FM Branch asked DFO Science to determine the PA compliance of the proposed reference points and decision rules. In addition, FM requested a recommendation for the management of these stocks for the 2024 fishing season based on this new PA. This Science Response results from the regional peer review of October 25, 2023 on the review of the precautionary approach and projected harvest level options for northern shrimp stocks in the Estuary and Gulf of St. Lawrence.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".