Maternal and seasonal differences in egg sizes and spawning activity of northwest Atlantic haddock (<i>Melanogrammus aeglefinus</i>) in relation to body size and condition
Bibliographic record
Abstract
Egg and larval production of 22 captive spawning pairs of northwest Atlantic haddock (Melanogrammus aeglefinus) were monitored. Females spawned an average of nine egg batches (range 316) with a mean batch fecundity of 60 000 eggs and mean total fecundity of 535 000 eggs. Mean spawning duration was 37 days with a mean batch interval of 5.4 days. In multiple linear regression, male Fulton's condition factor (range 1.101.55) and mean batch interval explained 56% of variation in fertilization rate (33% and 23%, respectively). Seasonal composite egg diameter spanned 1.371.53 mm among females. Mean egg diameter within females declined seasonally by an average of 10.4% (37% by volume). Females produced 46 larvae per gram body weight. Body weight was the single best predictor of fecundity (r2 = 0.57), with Fulton's condition factor (range 1.041.76) explaining no significant additional variation over length or weight. Length and condition explained 39% of variation in seasonal composite egg diameter (22% and 17%, respectively) and body weight independently explained 32%. Sex-specific parental condition and body size acted through large egg size and elevated fertility to enhance reproductive output. Male spawning success was more sensitive than egg production to changes in condition.
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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 | 0.000 | 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".