RESULTS OF A PILOT STUDY MONITORING NORTHERN SAW-WHET OWL MIGRATION IN CENTRAL ALBERTA, CANADA
Bibliographic record
Abstract
We initiated monitoring of Northern Saw-whet Owl (Aegolius acadicus) migration by mist-netting at Beaverhill Lake Natural Area, Alberta, Canada, with a part-time effort in 1997, 2000, and 2001. On the basis of positive results in those years we expanded the study to nightly netting following a standardized protocol in fall 2002 and 2003. Those years yielded 145 and 151 owls captured, respectively. First-year owls represented 68.7% of captures, and females represented 73.8% of captures (two-year mean). Migration began on 18 August, peaked on 3 October, and ended 11 November. Ninety-five percent of the owls were captured between 9 September and 4 November. There were three recaptures within a year and no recaptures in subsequent years.
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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".