The effect of different schedules of reinforcement on the structure of the black-capped chickadees’ chick-a-dee call.
Bibliographic record
Abstract
It is known that adult songbirds can modify the output and structure of their vocalizations in different behavioral contexts. However, whether changes in the abiotic environment (i.e., food availability) also affect vocal structure is less understood. Here we test whether the chick-a-dee calls of the black-capped chickadee differ between birds on two different schedules of reinforcement (continuous and partial) and in two different behavioral contexts (singing alone and mildly alarmed by human intrusion). Our results reveal differences in the composition and pitch of chick-a-dee calls from birds in different behavioral contexts and on different schedules of reinforcement. However, calls from birds on the different schedules of reinforcement become more similar when evoked by human intrusion. We suggest that these results may represent differences in the energy dedicated to call production. If vocal structure varies consistently with changes to the abiotic environment, we may be able to detect environmental changes (i.e., warming and reduction in available forage) through analysis of vocal traits. While we demonstrate differences in call structure based on schedules of reinforcement, results from field studies in multiple regions will divulge whether these vocal changes are consistent and useful for analysis of abiotic conditions.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".