Mate choice based on complex visual signals in the brook stickleback, Culaea inconstans
Bibliographic record
Abstract
In species with complex courtship, females often have the opportunity to assess multiple male cues during mate choice. Depending on the strength and form of the coevolutionary relationships between male traits and female preferences, geographic variation in signal complexes can result in a variety of mate choice scenarios ranging from partial to complete positive assortative mating. Using mate choice trials, we investigated the relationship between intrapopulation female biases for complex visual signals and interpopulation mating dynamics in 2 populations of brook stickleback, Culaea inconstans, from distinct mitochondrial DNA genetic lineages. Our results showed that courtship effort is the primary visual criterion of mate assessment in this species; females from both lineages exhibited directional preferences for increased behavioral vigor. In contrast, male nuptial color intensity and body size had little influence on female choice decisions. Interpopulation divergence in male traits was not strongly correlated with divergence in female preferences, producing asymmetric patterns of assortative mate choice across the lineage divide. We compare female preferences for male visual traits in C. inconstans with other members of the Gasterosteidae and suggest that mate assessment differs substantially between stickleback species.
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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 | 0.001 | 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".