A review of the importance of various areas for northern contingent West-Atlantic mackerel spawning
Bibliographic record
Abstract
Abstract The southern Gulf of St. Lawrence (sGSL) is considered to be the dominant spawning area of northern contingent West-Atlantic mackerel (Scomber scombrus). This premise underlies our basic understanding of the stock and its assessment. Because there are however indications of spawning outside the sGSL, we aimed to review the potential importance of various external regions for spawning, based on a weight of evidence approach. Fundamentally, important spawning areas can only exist where there is evidence of a considerable spawning stock biomass being present when environmental conditions are suitable for spawning. This should lead to direct observations of significant egg and larval densities. Based on an ensemble of evidence (migration patterns, environmental conditions, and ichthyoplankton observations), we investigated the dominance of the sGSL for northern contingent mackerel spawning. Elsewhere, such as on the Scotian Shelf, where mackerel starts its spring migration, there is evidence of minor but relatively consistent egg production. Spawning off Newfoundland, where mackerel can migrate to later in the year, appears sporadic and highly variable in intensity. This review should alleviate some of the uncertainty associated with the mackerel stock assessments and be a baseline to further our knowledge on mackerel spatial spawning dynamics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".