Stockenvironment recruitment models for Norwegian spring spawning herring (<i>Clupea harengus</i>)
Bibliographic record
Abstract
Different stockenvironment recruitment models for Norwegian spring spawning herring (Clupea harengus) are fitted to a time series of spawning stock, recruitment, and temperature data extending back to 1907. In addition to the traditional temperature index from the Barents Sea (the average annual temperature in the Kola transect), we also developed a new index based on the temperature in the larval drift trajectories during early larval life. The models show highly significant effects of both spawning stock and temperature. The inclusion of the temperature term in the stockrecruitment models removes the autocorrelation from the residuals and improves their explanatory ability by 69%. We explore the interdependence between recruitment success and subsequent spawning stock biomass and conclude that this is not likely to generate the stockrecruitment relationship. Our analysis suggests that the collapse of the Norwegian spring spawning herring stock in the period 19501970 was not caused by reduced recruitment, but by the drop in spawning stock biomass induced by the increased fisheries in this period.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".