Validation of a Method for Quantifying Male Mating Preferences in the Guppy (Poecilia reticulata)
Bibliographic record
Abstract
Male and female mating preferences are commonly inferred from association times spent with potential mates in a dichotomous-choice test. However, this assessment method is rarely validated, particularly so for male mating preferences. Using the Trinidadian guppy (Poecilia reticulata), an important model species in the study of sexual selection, we tested whether a male’s mating preference for either of two stimulus females in a dichotomous-choice test predicted his mating behaviours directed at the preferred female when he was allowed to swim freely with both females. First, we presented individual males with two females that differed in body length in a dichotomous-choice apparatus in which the male could only use visual cues to assess the paired females. We quantified male mating preference as the duration of time a focal male spent associating with each female. Immediately following this test, the focal male was allowed to swim freely with both females, and we quantified the time he spent sexually pursuing each female and the number of courtship sigmoid displays and copulation attempts he directed at each female. On average, males did not significantly prefer either of the two stimulus females in either of the two tests; however, the magnitude of male preference for the larger female tended to increase as the size difference between the paired females increased. More importantly, there was a significant positive relationship between male association time in the dichotomous-choice test and both the time spent sexually pursuing and the number of courtship sigmoid displays directed at the same female initially preferred in the dichotomous-choice test. Collectively, these results confirm that association time measured in a dichotomous-choice test is a reliable predictor of male mating preferences in the Trinidadian guppy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".