Ectoparasites in lekking Sharp-tailed Grouse, Tympanuchus phasianellus
Bibliographic record
Abstract
To investigate the validity of assumptions based on the parasite avoidance model, fifty-two male Sharp-tailed Grouse (Tympanuchus phasianellus) collected in northern Ontario from six separate leks were examined.Ectoparasitic burdens were recorded along with traits (feather damage, hematomas, body condition, body mass) and cues (territorial position, age) which may be used by the female to discriminate among males for their parasite loads.Neither assumption of the transmission avoidance model.was met.Little variation in ectoparasite number existed in the breeding population as a whole or within individual leks.None of the traits or cues measured were correlated consistently with ectoparasitic burdens.These results suggest that randomly mating females would, on "average," mate with lightly infested individuals.Therefore, benefit to a discriminating female Sharp-tailed Grouse would be negligible.
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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 | 0.000 |
| 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".