Bibliographic record
Abstract
Dichoptic masking was compared between luminance and contrast domains using the modified dichoptic probed-sinewave paradigm. A brief letter (16.6ms) was presented to one eye while a sinusoidally varying (luminance or contrast) masker was dichoptically presented to the other eye. The contrast detection threshold of the letter was measured at various times (phases) with respect to the flickering masks. Three flickering frequencies (1, 2, 3 Hz) and four different types of maskers were used: (1) a large uniform-field luminance-defined masker, (2) an equivalent-sized contrast-defined masker that had a 1/f power spectrum, (3) a small localized contrast masker that covered the letter area only,(4) a surround contrast masker whose area is equal area(2)-area(3). The results showed that luminance maskers generally increased the detecting threshold but not in a luminance-dependent manner. On the other hand, thresholds did vary in a contrast-dependent manner for both (2) and (3). No contrast-dependent modulation was found for (4). Our results suggest that dichoptic masking can come in at least two forms: luminance-based and contrast-based. In the former, dichoptic masking is sustained whereas in the latter it is more localized in time and space. Meeting abstract presented at VSS 2012
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".