Detection and discrimination of texture modulations defined by orientation, spatial frequency, and contrast
Bibliographic record
Abstract
We sought to determine whether the detection and the identification of texture modulations are mediated by a common mechanism. On each trial two textures were presented, one of which contained a modulation in orientation (OM), spatial frequency (FM), or contrast (CM). Observers were required to indicate whether the modulated texture was presented in the first or the second interval as well as the nature of the texture modulation. The results showed that for two of the three pairwise matchings (OM-FM and OM-CM) detection and identification performance were nearly identical, suggesting a common underlying mechanism. However, when FM and CM textures were paired, discrimination thresholds were significantly higher than detection thresholds. In the context of the filter-rectify-filter model of texture perception, our results suggest that the mechanisms underlying detection are labeled with respect to their first-order input; i.e., the identities of these mechanisms are available to higher levels of processing. Several possible explanations for the misidentification of FM and CM at detection threshold are considered.
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".