Sensitivity to Information Conveyed by Horizontal Contours is Correlated with Face Identification Accuracy
Bibliographic record
Abstract
We measured thresholds in a 1-of-10 face identification task in which stimuli were embedded in orientation-filtered Gaussian noise. For upright faces, the threshold elevation produced by the masking noise varied as a function of noise orientation: significantly greater masking was obtained with horizontal noise than with vertical noise. However, the orientation selectivity of masking was significantly less with inverted faces. The performance of an ideal observer was qualitatively similar to human observers viewing upright faces: the masking function exhibited a peak for horizontally oriented noise although the selectivity of masking was greater than what was observed in human observers. These results imply that significantly more information about facial identity was conveyed by horizontal contours than by vertical contours, and that human observers use this information more efficiently to identify upright faces than inverted faces. We also found a significant positive correlation between selectivity for horizontal information and face identification accuracy for upright, but not inverted faces. Finally, there was a significant positive correlation between horizontal tuning and the size of the face inversion effect. These results demonstrate that the use of information conveyed by horizontal contours is associated with face identification accuracy and the magnitude of the face inversion effect.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".