Mechanisms regulating oocyte recruitment and skipped spawning in Northeast Arctic cod (Gadus morhua)
Bibliographic record
Abstract
To examine mechanisms that affect fecundity, atresia, and skipped spawning in Northeast Arctic cod ( Gadus morhua ), we conducted an experiment where wild-caught cod (>60 cm) kept under restricted food regimes were subjected to monthly biopsies and hormonal and physical measurements. The power of body weight as a fecundity proxy increased until the presumed end of follicle proliferation in early November; thereafter, it remained stable. Atresia occurred in most females, but for maturing females, mainly close to spawning. Eighteen percent of the females had small gonads with predominantly previtellogenic oocytes at sacrifice in January. These females were past-spawners, verified by postovulatory follicles in their gonads. These “skippers” had lower condition than maturing cod from December, smaller livers upon sacrifice, and lower plasma 17β-estradiol values from early November. Until November, oocytes developed similarly for all females, but in November, oocyte development was arrested at the early cortical alveoli stage and atresia occurred in all skippers. In summary, fecundity and skipped spawning seem highly influenced by energy reserves during early vitellogenesis and was limited to females only. Finally, skippers were identifiable long before the predicted onset of spawning, which could have implications for forecasting of egg production and hence stock–recruitment relationships.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".