Bibliographic record
Abstract
A database of voice-prints for individual Hermit Thrush birds was developed and used to acoustically identify them from one breeding season to the other. A method was used to obtain audio recordings from birds in the most non-intrusive way possible. Birds that were located near roads or park trails were recorded and no birds were branded, marked, stalked, or flushed out of hiding. All the audio recordings were made using Sony digital video camera recorders and the sampling rate was 48 kHz with 16 bit quantization. The camera was pointed in the direction of the sound source when the bird was not visible. Audio files in 'wav' format were extracted from Digital 8 and Mini DV video cassettes were used by the DCR-TRV525 and DCR-VX2100 cameras. Spectral analysis was carried out using the Raven 1.2.1 interactive sound analysis software. It was found that a Hermit Thrush song began with an introductory note, followed by a series of flute-like body notes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".