Hearing threshold shifts and recovery in harbor seals (<i>Phoca vitulina</i>) after octave-band noise exposure at 4 kHz
Bibliographic record
Abstract
Safety criteria for underwater sounds from offshore pile driving are needed to protect marine mammals. As a first step toward understanding effects of impulsive sounds, two harbor seals were exposed to octave-band white noise centered at 4 kHz at three mean received sound pressure levels (SPLs; 124, 136, and 148 dB re 1 μPa) at up to six durations (7.5, 15, 30, 60, 120, and 240 min); mean received sound exposure level (SEL) range was 166-190 dB re 1 μPa(2) s. Hearing thresholds were determined before and after exposure. Temporary hearing threshold shifts (TTS) and subsequent recovery were quantified as changes in hearing thresholds at 1-4, 4-8, 8-12, 48, and 96 min after noise exposure in seal 01, and at 12-16, 16-20, 20-24, 60, and 108 min after exposure in seal 02. Maximum TTS (1-4 min after 120 min exposure to 148 dB re 1 μPa; 187 dB SEL) was 10 dB. Recovery occurred within ~60 min. Statistically significant TTSs (>2.5 dB) began to occur at SELs of ~170 (136 SPL, 60 min) and 178 dB re 1 μPa(2) s (148 SPL, 15 min). However, SEL is not an optimal predictor of TTS for long duration, low SPL continuous noise, as duration and SPL play unequal roles in determining induced TTS.
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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 | 0.000 | 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 | 0.001 |
| 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".