Capturing nuisance urban Canada geese using the bird immobilizing agent alpha-chloralose in Reno, Nevada: What we learned
Bibliographic record
Abstract
This paper discusses several challenges Wildlife Services (WS) personnel encountered while conducting alpha-chloralose (AC) treatments on Canada geese in Reno, Nevada during May and June 2003. While the WS AC training manual provides guidelines for the safe and effective anesthetization of Canada geese using this chemical immobilization tool, we encountered and solved problems and challenges that had not been reported in previous reports on projects using AC. Problems we encountered ranged from being accosted by drunks to interrogations by “elderly ladies” worried that we might be taking their favorite goose. Challenges in collecting immobilized geese resulted from river currents and their effect on AC-treated geese, moss entangling the boat motor propeller on ponds, and automatic sprinklers turning on at inopportune times. It is hoped that addressing these real-world experiences can help others become more proficient in AC field use.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".