Temporal aspects of orientation pooling using visual noise stimuli
Bibliographic record
Abstract
Previous psychophysical studies have shown that oriented signals are pooled over space to support better perceptual performance. We have investigated whether oriented signals may also be pooled over time. Using an orientation-in-noise paradigm, the threshold to discriminate large orientation differences was measured as the minimum amount of signal required to discriminate an oriented stimulus from unoriented noise. Discrimination thresholds were better with dynamic stimuli, containing multiple independent samples over time, than with static stimuli presented for an equal duration. Thresholds for dynamic stimuli showed gradual improvement from very brief (12 ms) to remarkably long presentation times (>4 s). Spatial integration of orientation signals is very efficient and can be understood in terms of a model based on signal detection theory, with performance limited by early and late stages of intrinsic noise. The nature of temporal integration is different, however, and is more consistent with probability summation of the outputs from low-level orientation detectors operating at a very brief timescale but whose outputs can be combined over a very long duration to yield better perceptual performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".