Fecundity, atresia, and spawning strategies of Atlantic herring (Clupea harengus)
Bibliographic record
Abstract
Atlantic herring ( Clupea harengus ) have contrasting spawning strategies, with apparently genetically similar fish “choosing” different spawning seasons, different egg sizes, and different spawning areas. In the North Sea, both autumn- and winter-spawning herring share the same summer feeding area but have different spawning areas. Females of both spawning types start their oocyte development in April–May. Oocyte development is influenced by the body energy content; during the maturation cycle, fecundity is down-regulated through atresia in relation to the actual body condition. Hence, fecundity estimates must account for the relative time of sampling. The down-regulation over the whole maturation period is approximately 20% in autumn- and 50% in winter-spawning herring. The development of the oocytes is the same for both spawning strategies until autumn when autumn spawners spawn a larger number of small eggs. In winter spawners, oocyte development and down-regulation of fecundity continues, resulting in larger eggs and lower number spawned. In theory, autumn and winter spawners could therefore switch spawning strategies, indicating a high level of reproductive plasticity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".