"Go" Signal Intensity Influences the Sprint Start
Bibliographic record
Abstract
INTRODUCTION: Loud sounds can decrease reaction time (RT) and increase force generated during voluntary contractions. Accordingly, we hypothesized that the loud starter's pistol at the Olympic Games allows runners closer to the starter to react sooner and stronger than runners farther away. METHODS: RT for the 100/110 m athletics events at the 2004 Olympics were obtained from International Association of Athletics Federations archives and binned by lane. Additionally, 12 untrained participants and four trained sprinters performed sprint starts from starting blocks modified to measure horizontal force. The "go" signal, a recorded gunshot, was randomly presented at 80-100-120 dB. RESULTS: Runners closest to the starter at the Olympics had significantly lower RT than those further away. Mean RT for lane 1 (160 ms) was significantly lower than for lanes 2-8 (175 +/- 5 ms), and RT for lane 2 was significantly lower than that for lane 7. Experimentally, increasing "go" signal intensity from 80-100-120 dB significantly decreased RT from 138 +/- 30 to 128 +/- 25 to 120 +/- 20 ms, respectively. Peak force was not influenced by sound intensity. However, time to peak force was significantly lower for the 120 dB compared to the 80-dB "go" signal for untrained but not trained participants. When a startle response was evoked, RT was 18 ms lower than for starts with no startle. Startle did not alter peak force or time to peak force. CONCLUSION: Graded decreases in RT may reflect a summation-mediated reduction in audiomotor transmission time, whereas step-like decreases associated with startle may reflect a bypassing of specific cortical circuits. We suggest that procedures presently used to start the Olympic sprint events afford runners closer to the starter the advantage of hearing the "go" signal louder; consequently, they react sooner but not more strongly than their competitors.
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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 | 0.001 |
| 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".