Science response: stock status update of American lobster in LFA 33
Bibliographic record
Abstract
The scientific basis for assessing the status of American Lobster (Homarus americanus) stocks in Lobster Fishing Areas (LFAs) 27–33 was examined at a framework meeting on January 23–24, 2018 (Cook et al. 2020). This was followed by an assessment held on October 1, 2018, that provided advice only for LFA 33, to align timing of science advice with data availability and the fisheries management cycle (DFO 2019). The Framework Review identified and agreed upon primary, secondary, and contextual indicators to be used for the assessment of this stock. Some indicators are directly linked to stock health and status (e.g., abundance), whereas others describe the population characteristics (e.g., size structure) or ecosystem considerations (e.g., temperature). For the purposes of a stock status update, only the primary and secondary indicators are reported. Contextual biological (maximum/median size, sex ratios, etc.) and environmental (bottom temperature) indicators are not presented here. This Science Response Report results from the Regional Science Response Process of October 7, 2021, on the Stock Status Update of American Lobster in Lobster Fishing Area (LFA) 33. When this document was written, there were outstanding commercial fishing and recruitment trap project logs. As such, some results are preliminary as detailed below.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.023 |
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".