Using automated sound recording and analysis to detect bird species‐at‐risk in southwestern Ontario woodlands
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT We conducted a field study to compare the effectiveness of acoustic recordings coupled with automated sound recognition versus traditional point counts in terms of their relative abilities to detect 3 bird species‐at‐risk in southwestern Ontario, Canada. The comparison was made in 50 woodlots, each of which contained a standard Forest Bird Monitoring Program plot of 5 point‐count stations. An automated recording device was present at one of the point‐count stations. We found that the automated recording and analysis system worked at least as well as the more traditional point‐count method in identifying woodlots containing acadian flycatcher ( Empidonax virescens ) and cerulean warbler ( Setophaga cerulea ), but that both methods combined performed better than either method alone. The automated system also required considerably less effort in the field (a difference of 140 min/woodlot) with very little additional effort identifying vocalizations in the lab (approx. 22.5 min/woodlot, for all 3 species combined). The automated system was not as effective in detecting prothonotary warbler ( Protonotaria citrea ), possibly because the species is much less common in southern Ontario than the other 2 species. © 2014 The Wildlife Society.
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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 it