Systematic bias in estimates of reproductive potential of an Atlantic cod (<i>Gadus morhua</i>) stock: implications for stockrecruit theory and management
Bibliographic record
Abstract
Stockrecruit relationships that use spawning stock biomass (SSB) to represent reproductive potential assume that the proportion of SSB composed of females and the relative fecundity (number of eggs produced per unit mass) are both constant over time. To test these two assumptions, female-only spawner biomass (FSB) and total egg production (TEP) were estimated for the Northeast Arctic stock of Atlantic cod (Gadus morhua) over a 56-year time period. The proportion of females (FSB/SSB) varied between 24% and 68%, and the variation was systematic with length such that SSB became more female-biased as the mean length of spawners increased. Relative fecundity of the stock (TEP/SSB) varied between 115 and 355 eggs·g1and was significantly, positively correlated with mean length of spawners. Both FSB and TEP gave a different interpretation of the recruitment response to reductions in stock size (overcompensatory) compared with that obtained using SSB (either compensatory or depensatory). There was no difference between SSB and FSB in the assessment of stock status; however, in recent years (19802001) TEP fell below the threshold level at which recruitment becomes impaired more frequently than did SSB. This suggests that using SSB as a measure of stock reproductive potential could lead to overly optimistic assessments of stock status.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".