Reconstructing salmon growth trajectories through biochronologies across a highly variable growthscape
Bibliographic record
Abstract
Measuring the growth of migratory fish across habitats is difficult because field observations only provide a snapshot into their life; yet, understanding which habitats provide better growth opportunities is crucial for their conservation. We experimentally enclosed individually tagged juvenile Chinook salmon ( Oncorhynchus tshawytscha) in habitats with known differences in growth potentials to evaluate four different models (Dahl–Lea, Fraser–Lee, Biological Intercept, and Modified Fry) used to back-calculate size-at-age from otoliths. We found that otolith-derived fish size reconstructions were most accurate using the Biological Intercept or Modified Fry model, though bias remains for slow growing fish. This tool was then used in a case study to reconstruct the mosaic of inter- and intra-habitat growth opportunities available to fishes, providing a useful framework for assessing and monitoring fish responses to habitat restoration and a changing environment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".