A loud acoustic stimulus is less likely to elicit a startle reflex when presented through headphones
Bibliographic record
Abstract
Prepared responses can be involuntarily triggered at short latency following the presentation of a loud (114-124 dB) startling acoustic stimulus (SAS), a phenomenon known as the “StartReact” effect. However, the origin of startle stimulus may impact its effectiveness in producing a startle. The present experiment used matched intensity stimuli originating from different directions to determine if differences exist in the probability of eliciting a startle reflex, as well as its amplitude. Participants performed a simple reaction time (RT) task requiring a wrist extension movement following a visual go-signal where a SAS (115 dB) was occasionally presented 200ms prior to the go-signal through headphones, or from loudspeakers located in front and behind the participant. Results indicated that there was a significantly lower probability of eliciting startle when the SAS was presented through headphones, but no difference in the probability, expression, or RT facilitation of a startle reflex when the SAS was presented via a loudspeaker in front or behind participants. Because participants were unable to determine the origin of the SAS from when delivered through the speakers, a follow-up experiment was performed where participants were aware of the origin of the SAS. Results showed that the probability of eliciting a startle reflex, as well as its amplitude, was moderately higher when the SAS was presented from the front versus the back. These results suggest that standard acoustic intensity measurements are potentially insufficient for gauging the true magnitude of an intense stimulus reaching the auditory apparatus.
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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 | 0.004 |
| 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) | 0.003 | 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".