How long does it take for the visual environment to influence the perceptual upright?
Bibliographic record
Abstract
The perceptual upright (PU) (the orientation in which objects appear ‘upright’) is influenced by visual and non-visual cues concerning the orientation of an observer. The orientation of the visual background accounts for about 25% of the influence. How long does it take for the perception of upright to form? We used the OCHART method (Dyde et al. 2004 Exp Brain Res. 173: 612) in which subjects identified a character (p/d) the identity of which depended on its orientation. Using a three-field tachistoscope (Ralph Gerbrands, field of view 6.3 degs) subjects viewed the character against a background. Display times were varied from 50–600ms and were immediately followed by a mask. We used the method of constant stimuli with a range of character and background orientations each presented at least six times. From this, we could identify the orientation where the character was most easily identified (PU). There was no effect of the background at the shortest exposure times, even though the subject could comfortably identify the character. There was an increase in the size of the effect with increasing exposure duration with a time constant of about 200ms. Subjects are able to identify the gist of a background with an exposure of only 26ms (Joubert et al. 2007 Vis Res. 47: 3286). However, using information from the visual background to influence character recognition seems to take substantially longer than this. It is possible that different types of orientation cues differ in the time they take to be effective.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".