Bibliographic record
Abstract
Purpose: Is perceptual space coded in the reference frame of the eye, head, body or space? We moved eyes with respect to head, the head with respect to a stationary body, the body with respect to a stationary head and both the head and body with respect to space to separate the head, body and space frames. Method: Auditory (60L-60R) targets were presented when eyes, head and body were pointing straight ahead. Subjects adjusted the interaural intensity ratio of 1kHz, 15ms sound bursts presented through headphones to indicate the remembered position of these targets relative to the head after actively moving their head, body (with head restrained) or both head and body together. Results: There was a significant shift in localization with head position (0.023db/deg, equivalent to approx. 2.3 deg/deg head rotation in the direction of head eccentricity, p<0.0001). A similar effect was also observed when the head was fixed in space while body position was changed. Moving the eyes with respect to the head, and body and head together had no effect on auditory localization judgments. Conclusions: Perceptual localization requires head-on-body, but not body-in-space information indicating the use of a body reference frame. CR: none. Supported by: Natural Science and Engineering Research Council (NSERC) of Canada and the Centre for Research in Earth and Space Technology (CRESTech) of Canada.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".