Information to support the assessment of Northern Shrimp, Pandalus borealis, and Striped Shrimp, Pandalus montagui, in the Eastern and Western assessment zones, February 2023
Bibliographic record
Abstract
The status of the Northern Shrimp (Pandalus borealis) and Striped Shrimp (P. montagui) resources in the Eastern Assessment Zone (EAZ) and the Western Assessment Zone (WAZ) were assessed based on the results of fishery-independent surveys jointly conducted by Fisheries and Oceans Canada (DFO) and the Northern Shrimp Research Foundation (NSRF) and commercial catch information. Data for the EAZ assessment spans the years 2009–2022 while the current WAZ time series began in 2014. Results from individual survey areas within the EAZ are also provided. Pandalus borealis stock in the EAZ is currently above the established Limit Reference Point (LRP; 15,800 t), but below the proposed Upper Stock Reference (USR). Based on the proposed USR of 31,600 t, this would place the stock in the cautious zone with a 98.3% probability. Both the reported and potential exploitation rates were the highest in the time series. The reported exploitation rate index for 2022/23 was 19.4% with 67% of the Total Allowable Catch (TAC) taken. Should the entire 2022/23 TAC of 10,732 t be taken, the potential exploitation rate index would be 29.1%. Pandalus montagui stock in the EAZ is currently well above the established LRP (3,100 t) and the proposed USR (6,100 t). This would place the stock in the healthy zone with a 93.1% probability. The full 2022 TAC of 1,400 t has been reported as catch, resulting in a 9.9% exploitation rate. Pandalus borealis stock in the WAZ is currently well above the established LRP (4,100 t) and the proposed USR (8,200 t). This would place the stock in the healthy zone with a 98.8% probability. The reported exploitation rate index for 2022/23 was 1.3% with 8.0% of the TAC taken. Should the entire 2022/23 TAC of 3,958 t be taken, the potential exploitation rate index would be 16.5%. Pandalus montagui stock in the WAZ is currently well above the established LRP (12,300 t) and the proposed USR (24,600 t). This would place the stock in the healthy zone with a > 99.9% probability. The reported exploitation rate index for 2022/23 was 10.7% with 92.6% of the TAC taken. Should the entire 2022/23 TAC of 12,096 t be taken, the potential exploitation rate index would be 11.5%.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".