TIME-EXPANSION AND ZERO-CROSSING PERIOD METER SYSTEMS PRESENT SIGNIFICANTLY DIFFERENT VIEWS OF ECHOLOCATION CALLS OF BATS
Bibliographic record
Abstract
We compared 2 bat detecting systems that use condenser microphones, 1 that performed computer analysis (Anabat6) of the output of a zero-crossing period meter (Anabat system) and the other that performed computer analysis (Canary 1.2) of the output of slowed-down (= time-expanded) recordings (Racal system). The 2 systems provided significantly different pictures of both numbers and characteristics (highest frequency, lowest frequency, and duration) of echolocation calls, whether recorded from free-flying bats in the field or from a stationary bat in the laboratory. Although the AnabatII detector was slightly more sensitive than the QMC S200 detector, the Racal system detected more echolocation calls than the Anabat system; the 19-dB difference in sensitivity was associated with a zero-crossing period meter in the Anabat system. Results suggest 2 recommendations. First, that analysis using zero-crossing period meters should not be used to describe echolocation behavior or calls of bats. Second, that studies of activity and use of habitat based on analysis using zero-crossing period meters should involve calibration against more sensitive bat-detecting systems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".