Local song elements indicate local genotypes and predict physiological condition in song sparrows<i>Melospiza melodia</i>
Bibliographic record
Abstract
Geographical variation in birdsong is taxonomically widespread and behaviourally salient, with females often preferring local over non-local song. However, the benefits associated with this preference remain poorly understood. One potential explanation is that song may reflect a male's place of origin and thus allow females to obtain genes well adapted to the local environment. We studied naturally occurring variation in the degree to which the elements of a male's song repertoire matched those of the local population ('syllable sharing') in migratory song sparrows (Melospiza melodia melodia). Syllable sharing was correlated with genetic similarity to the local population, suggesting that song reflects population of origin. Males sharing more syllables also had larger testosterone-dependent traits, fewer blood-borne parasites and reduced indicators of stress. Our findings are consistent with locally good genes models. Alternatively, immigrants' condition may suffer due to unfamiliarity with the breeding site or inability to match song elements during territorial interactions. Females preferring 'local-sounding' males may thus obtain genetic and/or direct benefits for their offspring.
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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 | 0.000 | 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".