Nothing more than a curve: a common mechanism for the detection of radial and non-radial frequency patterns?
Bibliographic record
Abstract
Radial frequency (RF) patterns, which are sinusoidal modulations of a radius in polar coordinates, have been frequently used to study shape perception. Discriminating RF patterns from circles could be accomplished either by mechanisms sensitive to local parts of the pattern, or by a global mechanism operating at the scale of the entire shape. Previous studies have argued that the detection of RF patterns could not be achieved by local curvature analysis, but instead by a specialized global mechanism for RF shapes. Here we challenge this hypothesis and suggest a model based on the detection of local curvature to account for the pattern of thresholds observed for both radial and non-radial (e.g. modulated around a straight line) frequency patterns. We introduce the Curve Frequency Sensitivity Function, or CSFF, which is characterized by a flat followed by declining response to curvature as a function of modulation frequency. The decline in response to curvature at high modulation frequencies embodies the idea of a perceptual limitation for high curve frequencies. The CSFF explains the initial decrease in detection thresholds for low RFs followed by the asymptotic thresholds for higher RFs (Wilkinson, Wilson, & Habak, 1998) and similarly accounts for results with non-radial frequency patterns (Prins, Kingdom, & Hayes, 2007). In summary, our analysis suggests that the detection of shape modulations is processed by a common curvature-sensitive mechanism that is independent of whether the modulation is applied to a circle or a straight line and that therefore radial frequency patterns are not special. Meeting abstract presented at VSS 2016
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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 | 0.000 | 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".