Application of otolith increment analysis to the study of maturation timing in female kokanee salmon
Bibliographic record
Abstract
I investigated the influence of growth history on the expression of female reproductive tactics in kokanee salmon (Oncorhynchus nerka) from Meadow Creek Spawning Channel, British Columbia, Canada. Female kokanee either arrive at the spawning area with red nuptial coloration, or less commonly, sexually immature with silver coloration. Silver- and red-arriving females may reflect different reproductive strategies in the population. I used otolith increment measurements to determine fish growth. In contrast to earlier studies, silver- and red-arriving females in 2013 did not differ in age at maturity (mostly were age 3+) or size at maturity (length from eye to tail, silver: 243.50 ± SE = 0.26 mm, red: 247.06 ± SE = 0.19 mm). In terms of females maturing at age 3+, silver- and red-arriving fish did not show a difference in any size-at-age or growth increment-at-age. This study indicates that growth is unlikely to influence the reproductive tactic adopted by spawning female kokanee salmon. Further research should focus on energy allocation differences during the pre-reproductive stages, and the heritability of the silver- and red-arriving tactics in female kokanee.
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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) | 0.000 | 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 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".