Concordant estimates of countergradient growth variation in striped bass (<i>Morone saxatilis</i>) using comparative life-history data
Bibliographic record
Abstract
Latitudinal growth compensation (i.e., countergradient growth) is increasingly suspected to be pervasive across diverse taxa. However, a major challenge limiting wider exploration of this topic lies in the difficulty of quantifying these relationships. Common garden experiments, and ideally genetics, remain the only true methods for understanding the genetic basis for compensatory growth. However, previous research suggests that comparative life-history data might produce concomitant, albeit nonconfirmatory, results on countergradient growth variations. However, there have been no evaluations of the precision of such estimates against those that are experimentally derived. I examined countergradient growth variations using comparative size-at-age data for striped bass ( Morone saxatilis ), a species for which experiments have already quantified countergradient growth patterns, and compared results derived from both techniques. The slope of the growth–latitude relationship for striped bass in eastern North America as measured with comparative data was virtually identical to that produced from experiments. Furthermore, comparative estimates of countergradient growth variations developed using a variety of metrics produced highly concordant results with one another. Comparative life-history data are not a replacement for experiments, but do provide valuable information on countergradient growth variations, especially for species and hypotheses not amenable to experimentation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".