Frame induced position shifts extend outside the frame in space but not in time
Bibliographic record
Abstract
When two probes are flashed at the same physical location within a moving frame, their perceived location can be offset by as much as the frame moves (Özkan et al, PNAS, 2021). Here we examine the extent of the frame’s influence in space and time. First, we positioned the flashed probes in front of or behind the frame in depth (or both) using red/cyan anaglyph glasses. The illusion strength was unaffected by these depth mismatches. In contrast, placing the flashed probes outside the frame did influence the illusion. The illusion strength dropped to 50% magnitude once the probes were 5.4 dva to the left of the frame. In the vertical direction, the 50% decrease required an offset of 6.9 dva between the frame and the probes. Offsets in time from the presentation of the frame caused a complete loss of the illusion. The frame was presented for one to three cycles of left-right motion and when the probes were flashed before or after the frame presentation, there was no illusion, no matter how long the frame had been present. This suggests that the illusion depends on immediately present sensory information without any influence of the frame’s motion before or after its actual presence on the screen. In conclusion, the frame effects do extend outside the boundaries of the frame in space but not in time.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".