Using microphone arrays and a new localization workflow to determine critical habitat and microhabitat of landbirds in a boreal forest ecosystem
Bibliographic record
Abstract
Biodiversity is declining rapidly among North American landbirds. While population decreases are most evident in species at risk, steep declines in common avian species have also been observed and shown to have significant economic and ecological impacts. Basic data on distributions and habitat preferences are lacking for many species. Traditional methods used to obtain this information are limited by cost, accuracy, and human resources. Furthermore, traditional methods have a limited capacity to accurately estimate metrics such as population density and microhabitat selectively. Recently, microphone arrays have become a more affordable, portable, and capable method of obtaining this data. I deployed 110 microphone arrays in the Labrador portion of the Boreal Shield Ecozone. My objectives were to (1) demonstrate a new localization workflow using microphone arrays, (2) determine the relationships between habitat characteristics and avian community parameters, and (3) identify microhabitat features associated with two common species in steep decline, the Boreal Chickadee (Poecile hudsonicus) and the Cape May Warbler (Setophaga tigrina).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".