Egg cannibalism in capelin <i>Mallotus villosus</i> at beach and deep‐water spawning habitats in the north‐west Atlantic Ocean
Bibliographic record
Abstract
We investigated egg cannibalism in spawning capelin Mallotus villosus on the north-east Newfoundland coast during July 2012-2014, specifically whether sex, spawning condition (i.e., spawning or spent) and spawning habitat influenced egg cannibalism. Capelin spawning in deep-water were 4.5-14 times more likely to be cannibals than those at the beach, probably due to the higher spatial overlap of spawners and conspecific eggs within this habitat relative to beaches. Males were 2.1-3.7 times more likely to be cannibals than females, but female cannibals had more eggs per stomach. Spawning fish were 1.6-1.9 times more likely to be cannibals than spent fish, but spent female cannibals had more eggs per stomach relative to spawning males and females in either habitat. Findings suggest that cannibalism may be an important foraging strategy, especially at deep-water spawning habitat, possibly extending the spawning season for males or increasing the probability of post-spawning survival for females. Although 44% of sampled females and 50% of males were cannibals, the estimated mortality due to egg cannibalism was low (0.49-2.97% of eggs produced annually), suggesting that egg cannibalism does not influence recruitment to a great extent in Newfoundland capelin.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".