Identifying possible drivers of the abrupt and persistent delay in capelin spawning timing following the 1991 stock collapse in Newfoundland, Canada
Bibliographic record
Abstract
Abstract Spawning timing in fish is generally cyclical in temperate regions in order to increase the probability of matching larval occurrence with ideal environmental conditions. The capelin stock in Northwest Atlantic Fisheries Organization Divisions 2J3KL collapsed in 1990–1991 and has not recovered. This collapse was concomitant with collapses in groundfish stocks and cold oceanographic conditions. Using citizen science data, newspaper archives, grey and primary literature, and monitoring data, a century of capelin beach spawning times were compiled. Capelin beach spawning has been persistently 3 weeks later since the stock collapse. To identify potential predictors of capelin spawning timing, an exploratory analysis was conducted using environmental and biological variables and a period factor that categorized a year as either pre-collapse (1990 and earlier) or post-collapse (post-1990) in a step-wise multiple regression model. Spawning timing was predicted to be delayed in the post-collapse period when there were negative anomalies in the Newfoundland and Labrador Climate Index and summer (June–August) North Atlantic Oscillation, and when there was a decrease in mean length of the spawning population. The production of weak year-classes is predicted when spawning is delayed, suggesting that late spawning is severely inhibiting the recovery of the stock.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".