When and why do smallmouth bass abandon their broods? The effects of brood and parental characteristics
Bibliographic record
Abstract
Abstract Variation in brood abandonment was explored by conducting partial brood removals from smallmouth bass, Micropterus dolomieu Lacepède, nests in two north temperate lakes. In both lakes, percent of the brood removed had no effect on nest failure rates. Nest failure prior to offspring swim‐up was more common, but unrelated to brood size after removal, in the lake with higher post‐spawning mortality and lower growth and fecundity. Brood size after removal was negatively related to nest failure in the lake with high survival, growth and fecundity. Nests guarded by young males failed more frequently than those of old males, and young broods failed more frequently than old broods. Dynamic programming and logistic regression models developed to predict nest fate worked better for the lake with selective pressures that theoretically favoured abandonment (e.g. high post‐spawning mortality). Both models identified male age and brood age as important factors in predicting nest fates. Because nest success is related to the age of the parent, this could have consequences for overall nest success for populations with different demographics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".