Mate choice and visibility in the expression of a sexually dimorphic trait in a goodeid fish (<i>Xenotoca variatus</i>)
Bibliographic record
Abstract
Male Xenotoca variatus (Bean, 1887) have shiny scales ("speckles") on their flanks, the number of which varies within and among populations. Using fish from two localities with turbid water and two with transparent water, we tested whether differences in the number of speckles were associated with differences either in water turbidity or with the expression of female mate choice. We also tested whether female mate choice was influenced by water turbidity. In our sample the number of speckles and water turbidity were not associated. A test including all the populations in a combined (factorial) analysis showed that in clear water females exhibit a preference for visiting the male with the largest number of speckles of a pair, though no population differences were detected. When tested in clear water, females spent more time close to a male with more speckles; in this instance, males were from a clear-water locality and possessed many speckles. Our findings suggest that female mate choice might not contribute to the geographical variation in speckle number, but may instead be constrained by the transmissibility of the signal.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".