Short Call-broadcasts Fail to Detect Nesting Least Bitterns (Ixobrychus exilis)
Bibliographic record
Abstract
We conducted 11 call-broadcast surveys at one location in each of four wetlands, and detected an Ixobrychus exilis (Least Bittern) on only 9 of the 44 (20%) surveys, while the observer was located on average 50.1 m ± 19.7 SD (range = 25–75 m, n = 11 nests) from at least one active bittern nest during each survey. For 8 of 9 (89%) detections, at least one bittern was already vocalizing at the beginning of the survey, before the Least Bittern call was played. We show that it is possible for this species to remain undetected with the use of call-broadcasts that are less than 30 seconds, even though the species may be nesting as close as 25 m to the location from which the calls are broadcasted. We suggest that systematic nest searches are more reliable than call-broadcast surveys for detecting nesting Least Bitterns.
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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) | 0.000 | 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) | 0.001 | 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 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".