Call-note discriminations in black-capped chickadees (Poecile atricapillus).
Bibliographic record
Abstract
Bioacousticians (M.S. Ficken, S. R. Ficken, & S. R. Witken, 1978) classified black-capped chickadee call notes from the chick-a-dee call complex into 4 note types (A, B, C, and D) identified from sound spectrograms. In Experiment 1, chickadees (Poecile atricapillus) learned operant auditory discriminations both within and between the 4 note types but learned the between note-type discrimination significantly faster. In Experiment 2, when the original, unrewarded between-category exemplars were replaced with novel, rewarded exemplars of these same categories, chickadees showed transfer of inhibitory stimulus control to the novel exemplars. In Experiment 3, when novel exemplars were replaced by the original exemplars, chickadees showed propagation of positive stimulus control back to the original exemplars. This evidence suggests that chickadees and bioacousticians accurately sort conspecific call notes into the same open-ended categories (R. J. Herrnstein, 1990).
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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) | 0.001 | 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 | 0.001 | 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".