An Experimental Test of the Condition Dependent Handicap Hypothesis Using Gryllus Pennsylvanicus
Bibliographic record
Abstract
Viability-based indicator models predict a positive correlation between ornamentation and longevity.Although ornament manipulations can reveal attraction and survival effects, they can inaccurately estimate the costs of ornamentation arising from correlated life-history constraints.Cotton circumvented this problem by applying a weight manipulation to stalk-eyed flies and asking whether males with bigger stalks lived longer.She found that ornamentation was positively correlated with longevity in weight manipulated males.Building upon Cotton's findings, I applied a weight and a diet manipulation to field crickets (Gryllus pennsylvanicus) and quantified their acoustic signalling and longevity.High effort signallers survived longer across all treatments.Further, males that signaled more attractively also survived longer when they experienced a weight manipulation and/or a poor diet.The weight manipulation did not directly affect longevity, because weight manipulated males dealt with the manipulation by reducing their signalling effort.Overall, my results provide support for viability-based indicator models.academic, a competent writer, and in general be less accident prone.Though, despite her best efforts I still find a way to injure myself weekly.Without her assistance I would not have been able to complete my thesis.I
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".