THE OPPORTUNISTIC SERPENT: MALE GARTER SNAKES ADJUSTCOURTSHIP TACTICS TO MATING OPPORTUNITIES by
Bibliographic record
Abstract
Reproductivemales encounter potential mates under a range of circumstances that in uence the costs, bene ts or feasibility of alternative courtship tactics. Thus, males may be under strong selection to exibly modify their behaviour.Red-sided garter snakes (Thamnophis sir-talis parietalis) in Manitoba overwinter in communal dens, and court and mate in large aggre-gations in early spring. The number of males within a courting group varies considerably, as do the body sizes of both males and females.We manipulated these factors to set up replicated courtship groups in outdoor arenas, and analysed videotapes of 82 courtship trials to quantify courting behaviours of male snakes. Larger and more heavy-bodiedmales courted more vig-orously than did their smaller, thinner-bodiedrivals, and large females attractedmore intense courtship.The major effect, however, involved the number of rivalmales competing for copu-lation.Males in large groups not only reduced their overall vigour of courtship, but also mod-i ed their tactics in such a way as to bene t from the courtship activities of rival males. That is, they devoted less energy to inducing female receptivity (which requires energy-expensive caudocephalicwaving) and more effort to behaviour (tail-searching)that enhanced their own 2) Corresponding author’s
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".