A collection of stationary objects flashed periodically produce depth perception under ordinary viewing conditions
Bibliographic record
Abstract
We discovered that stationary objects flashed periodically produce depth perception under ordinary viewing conditions. We believe that small involuntary eye movements (Ko, Snodderly & Poletti, 2016) induce apparent motions of magnitudes proportional to the flash periods (for a similar proposal, see Gosselin & Faghel-Soubeyrand, 2017) and that these apparent motions are interpreted by the brain as a form of parallax that results normally from microscopic head movements (Aytekin & Rucci, 2012). Here, we tested a somewhat counterintuitive prediction of this hypothesis: perceived depth should increase linearly with viewing distance. Eight observers were shown, on an Asus VG278HR at a refresh rate of 120 Hz, a stimulus made of 200 white discs distributed randomly on a black background spanning 10 x 10 cm. Each disc flashed with one of 13 periods evenly spread between 8.33 ms and 108.33 ms; the period was chosen to be inversely proportional to the value of a depth map at the disc location. The depth map represented the thick vertices of a cube. All observers reported seeing clearly this volumetric shape during the experiment. Participants viewed the stimulus binocularly, sitting comfortably in a chair at distances of 45, 70, 95, 120, 145 and 170 cm, three times. On every trial, they were asked to move their chair at a randomly selected viewing distance indicated on the computer monitor. Viewing distances were marked on the floor with stripes of photoluminescent tape. When ready, subjects pressed on the computer mouse button to initiate the presentation of the stimulus for 2 s. Finally, they were instructed to estimate the perceived depth in the stimulus by adjusting the length of a horizontal line drawn on the computer monitor with the computer mouse. As expected, we found a strong positive linear relationship between viewing distances and mean depth estimations (r=0.9585, p=0.0025).
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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 | 0.001 |
| 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".