The contribution of nonvisual information to simple place navigation and distance estimation: An examination of path integration.
Bibliographic record
Abstract
In Experiment 1, participants walked without vision to a target location they had either previously viewed, were led to and from blindfolded, or both viewed and were led to and from blindfolded. A course to the target could be set and held without vision only if prior vision of its location was available. The locomotor group reproduced the heading and distance to the target less accurately than the other groups, which did not differ significantly. However, when nonvisual information accompanied vision of the target location, it served to subtly influence performance. Participants in Experiment 2 estimated the distance of a target they either viewed or were led to blindfolded. When vision was available, men overestimated target distance and women underestimated it. When target distance was learned nonvisually, no sex differences in distance estimations emerged. Our findings suggest that deriving navigation information from nonvisual locomotion is difficult and may be dependent on prior visual information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".