Frequency doubling illusion: detection vs. form resolution.
Bibliographic record
Abstract
PURPOSE: To investigate the difference between detection and form resolution thresholds for the frequency doubling (FD) illusion. METHOD: The right eyes of 20 normal healthy subjects (10 female; age range, 18 to 30 years; mean age, 24.05 years; SD, 1.39) were examined. Vertically oriented FD stimuli were presented at fixation and 10 degrees nasally using a dual temporal alternate forced choice method of constant stimuli (2AFC MOCS) to estimate the thresholds for detection and form resolution. Additional strategies for threshold estimation (yes/no, modified rapid estimation by binary search) were used to determine the detection threshold. The effect of subject instruction on the FD threshold was also examined. The test-retest characteristics were investigated by determining the coefficient of repeatability. RESULTS: Detection thresholds using 2AFC MOCS were 0.86 +/- 0.20 (+/-1 SE) Michelson contrast percentage (MC%) at fixation and 0.84 +/- 0.21 at 10 degrees. Form resolution thresholds using 2AFC MOCS were 1.08 +/- 0.23 MC% at fixation and 1.04 +/- 0.16 at 10 degrees . These thresholds were found to be significantly different at fixation (p = 0.004) and 10 degrees (p = 0.005). No difference was found between threshold estimation strategies, but subject instruction had a significant effect (fixation: 2.41 +/- 0.52 MC%, p < 0.001; 10 degrees : 2.19 +/- 0.48 MC%, p < 0.001). CONCLUSIONS: Detection thresholds were significantly lower than form resolution thresholds for the FD stimulus. This result is in agreement with classic FD studies and illustrates that the perception of flicker precedes the perception of the FD illusion at threshold.
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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 | 0.004 |
| 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 | 0.000 |
| 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".