Peer Review #1 of "Are some individuals generally more behaviorally plastic than others? An experiment with sailfin mollies (v0.1)"
Bibliographic record
Abstract
Individuals within the same population generally differ among each other not only in their behavioral traits but also in their level of behavioral plasticity (i.e. in their propensity to modify their behavior in response to changing conditions). If the proximate factors underlying individual differences in behavioral plasticity were the same for any measure of plasticity, as commonly assumed, one would expect plasticity to be repeatable across behaviors and contexts. Yet, this assumption remains largely untested. Here we conducted an experiment with sailfin mollies (Poecilia latipinna) whose behavioral plasticity was estimated both as the change in their personality traits or mating behavior across a social gradient and using their performance on a reversal-learning task. We found that the correlations between pairwise measures of plasticity were weak and non-significant, thus indicating that the most plastic individuals were not the same in all the tests. This finding might arise because either individuals adjust the magnitude of their behavioral responses depending on the benefits of plasticity, and/or individuals expressing high behavioral plasticity in one context are limited by neural and/or physiological constraints in the amount of plasticity they can express in other contexts. Because the repeatability of behavioral plasticity may have important evolutionary consequences, additional studies are needed to assess the importance of trade-offs between conflicting selection pressures on the maintenance of intra-individual variation in behavioral plasticity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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 teacher head, 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".