Visual and auditory processing of distance and the time-to-collision of an approaching object
Bibliographic record
Abstract
Information about the impending collision of an approaching object can be specified by visual and auditory means. We examined the discrimination thresholds for vision, audition, and vision/audition combined, in the processing of distance and the time-to-collision (TTC) of an approaching object. The stimulus consisted of a computer simulated car approaching on a flat ground towards the subject that was presented through a stereoscopic screen and stereo headphones. Subjects (Ss) either viewed, heard, or both viewed and heard, two approaching movements in succession (a reference and a comparison), which disappeared at a certain point before collision. Ss then pressed a button to indicate which of the two movements would result in the car arriving sooner OR having a shorter distance from the subject at the moment it disappeared. The TTC and distance were held constant for the reference stimulus, but varied for the comparison stimuli according to the method of constant stimuli, with the order of the two randomized. The approaching speed, the size and sound level of the car were also held constant for the reference stimulus but varied for the comparison stimuli. We analyzed the sensitivity to both the difference in TTC and the difference in distance for both the TTC task and the distance task. The results of both the TTC and distance tasks showed that Ss were more sensitive to the difference in TTC provided by vision than by audition, but more sensitive to the difference in distance provided by audition than by vision. The performance for the vision/audition combined condition was almost identical to the vision only condition for TTC sensitivity and almost identical to the auditory only condition for the distance sensitivity in TTC task only. This indicates that, when both cues are available, the most accurate source of information is used.
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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 | 0.002 |
| 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) | 0.002 | 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".