Visual detection of orientation modulators suggests limitations to scale invariance of second order mechanisms
Bibliographic record
Abstract
Using a second-order visual stimulus in which the orientation of a noise carrier was spatially modulated, we probed the relationship between the frequency of the band-pass filtered carrier and that of the envelope periodic spatial modulator. In a 2-AFC psychophysical detection task, we obtained the threshold tuning functions for both the carrier luminance contrast and the modulation depth for a range of ratios of the two frequency parameters using a foveally presented stimulus in a circular aperture. With a scale invariant neural mechanism, suggested for second-order stimuli, functions of the ratio of carrier and modulator frequencies should show consistent tuning, largely independent of the specific pair of frequency parameters. We found that was not the case. For the carrier contrast threshold, the functions showed a low-pass tuning when the carrier frequency was varied and band-pass tuning when the modulator frequency was varied. For both parametric manipulations, the ratio had a similar range of tested values. When we measured modulation depth thresholds with the stimuli controlled for luminance contrast detectability, the functions showed more modest differences in tuning. To exclude an explanation based on averaging of any optimal tuning spatially across the visual field, we repeated the measurements for a stimulus confined in eccentricity (Annulus, radius 14.6 deg of visual angle). That configuration was more difficult to detect and returned broadly similar tuning functions. These results do not support the idea of a constant coupling between the scales of mechanisms detecting the carrier and modulator that would be required for scale invariance.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".