The Saliency of Angular Shapes in Threatening and Nonthreatening Faces
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Bibliographic record
Abstract
Several lines of evidence suggest that angularity and curvilinearity are relied upon to infer the presence or absence of threat. This study examines whether angular shapes are more salient in threatening compared with nonthreatening emotionally neutral faces. The saliency of angular shapes was measured by the amount of local maxima in S(θ), a function that characterizes how the Fourier magnitude spectrum varies along specific orientations. The validity of this metric was tested and supported with images of threatening and nonthreatening real-world objects and abstract patterns that have predominantly angular or curvilinear features (Experiment 1). This metric was then applied to computer-generated faces that maximally correlate with threat (Experiment 2a) and to real faces that have been rated according to threat (Experiment 3). For computer-generated faces, angular shapes became increasingly salient as the threat level of the faces increased. For real faces, the saliency of angular shapes was not predictive of threat ratings after controlling for other well-established threat cues, however, other facial features related to angularity (e.g., brow steepness) and curvilinearity (e.g., round eyes) were significant predictors. The results offer preliminary support for angularity as a threat cue for emotionally neutral faces.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it