Statistical classification of black-capped (Poecile atricapillus) and mountain chickadee (Poecile gambeli) call notes.
Bibliographic record
Abstract
Both black-capped (Poecile atricapillus) and mountain chickadees (Poecile gambeli) produce a chick-a-dee call that consists of several distinct note types. In some regions, these 2 species live sympatrically, and it has been shown that 1 species will respond weakly to songs of the other. This suggests that chickadee song, and potentially other of their vocalizations, contains species-specific information. We tested the possibility that call notes were acoustically sufficient for species identification. Black-capped and mountain non-D notes were summarized as a set of 9 features and then analyzed by linear discriminant analysis. Linear discriminant analysis was able to use these notes to identify species with 100% accuracy. We repeated this approach, but with black-capped and mountain D notes that were summarized as a set of 4 features. Linear discriminant analysis was able to use these notes to identify species with 94% accuracy. This demonstrates that any of the note types in these chickadee calls possesses sufficient information for species classification.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".