Otolith Microstructure during the Early Life-History Stages of Brown Trout: Validation and Interpretation
Bibliographic record
Abstract
Abstract We examined the extent to which otolith microstructure provides an accurate estimate of age, growth, and early life history transitions during the period between hatching and 1 week after emergence in Brown Trout Salmo trutta exposed to natural variations in ambient water temperature. All fry analyzed possessed a prominent check on the observed date of hatching. After hatching, daily growth increments were visible on sagittal otoliths. There was no evidence for the formation of an emergence check mark and no statistically significant evidence that emergence and daily temperature fluctuations interacted to form check marks. However, daily temperature fluctuations may influence the formation of check marks, largely based on an observed increase in the proportion of fish possessing checks on the days following the two largest temperature fluctuations observed during the experiment. There was no evidence that feeding or stressing emergent fish contributed to the formation of an emergence check mark. The observed proportionality of somatic and otolith growth in conjunction with daily growth increments and the formation of a prominent hatch mark provides the opportunity to back-calculate somatic length distributions and to document the hatching, dispersal, growth, and survival of the early life history stages of Brown Trout in nature. Received May 3, 2012; accepted October 29, 2012
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".