Fish growth and degree-days II: selecting a base temperature for an among-population study
Bibliographic record
Abstract
The degree-day (DD) is a method of describing the thermal opportunity for growth and development and is becoming increasingly popular when comparing fish growth over large spatial scales (e.g., counter-gradient growth). Temperatures too cold to permit growth are excluded in the DD equation by incorporating a lower temperature threshold (To). However, there is no convention for choosing To, and unknown is the effect of an incorrect Toon how growth is perceived. We simulate data to demonstrate how an incorrect Tomay lead to differences in temperature-corrected growth rates among populations. These differences increase with the error in Toand the thermal range among simulated populations. We then show the same relationships in an analysis of length-at-age data from 81 walleye (Sander vitreus) populations in North America. Together, our results demonstrate that differences in temperature-corrected growth rates among populations can be a statistical artifact rather than a biological phenomenon, especially when populations are distributed over a large thermal gradient.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".