Southwest Nova Scotia/Bay of Fundy Herring : Management Strategy Evaluation Framework
Bibliographic record
Abstract
An approach for conditioning operating models (OMs) for the southwest Nova Scotia/Bay of Fundy (SWNS/BoF) Atlantic Herring (Clupea harengus) management strategy evaluation (MSE) was developed in 2020 (Carruthers et al. 2023). This document completes the MSE framework that will be used to evaluate the performance of candidate management procedures (MPs) for the SWNS/BoF Herring fishery by defining: 1) the MSE objectives and associated performance metrics for evaluating the objectives, 2) the reference set of OMs that will serve as a testbed for evaluating the performance of MPs, 3) the closed-loop simulation approach used for the evaluation of MPs, 4) the exceptional circumstance criteria for triggering an evaluation of the suitability of the advice from an MP, and 5) the proposed frequency and timing of interim-year updates to be provided between full peer-reviewed frameworks, and the recommended timing of the next framework. The application of the MSE framework is demonstrated in this document using a set of candidate MPs. Candidate MPs can continue to be developed and evaluated using this MSE framework.
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".