Natural and synthetic vocalizations of brown rat pups, <i>Rattus norvegicus,</i> enhance attractiveness of bait boxes in laboratory and field experiments
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Bibliographic record
Abstract
BACKGROUND: Rats are often neophobic and thus do not readily enter trap boxes which are mandated in rodent management to help reduce the risk of accidental poisoning or capture of non-target animals. Working with brown rats, Rattus norvegicus, as a model species, our overall objective was to test whether sound cues from pups could be developed as a means to enhance captures of rats in trap boxes. RESULTS: Recording vocalizations from three-day-old pups after removal from their natal nest with both sonic and ultrasonic microphones revealed frequency components in the sonic range (1.8-7.5 kHz) and ultrasonic range (18-24 kHz, 33-55 kHz, 60-96 kHz). In two-choice laboratory bioassays, playback recordings of these vocalizations induced significant phonotactic and arrestment responses by juvenile, subadult and adult female and male rats. The effectiveness of engineered 'synthetic' rat pup sounds was dependent upon their frequency components, sound durations and the sound delivery system. Unlike other speakers, a piezoelectric transducer emitting sound bursts of 21 kHz with a 63-KHz harmonic, and persisting for 20-300 ms, proved highly effective in attracting and arresting adult female rats. In a field experiment, a battery-powered electronic device fitted with a piezoelectric transducer and driven by an algorithm that randomly generated sound cues resembling those recorded from rat pups and varying in fundamental frequency (19-23 kHz), duration (20-300 ms) and intermittent silence (300-5000 ms) significantly enhanced captures of rats in trap boxes baited with a food lure and soiled bedding material of adult female rats. CONCLUSION: Our study provides proof of concept that rat-specific sound cues or signals can be effectively reproduced and deployed as a means to enhance capture of wild rats. © 2016 Society of Chemical Industry.
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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 it