Exploration of visual factors in the disgust-anger confusion: the importance of the mouth
Bibliographic record
Abstract
According to the perceptual-attentional limitations hypothesis, the confusion between expressions of disgust and anger may be due to the difficulty in perceptually distinguishing the two, or insufficient attention to their distinctive cues. The objective of the current study was to test this hypothesis as an explanation for the confusion between expressions of disgust and anger in adults using eye-movements. In Experiment 1, participants were asked to identify each emotion in 96 trials composed of prototypes of anger and prototypes of disgust. In Experiment 2, fixation points oriented participants' attention toward the eyes, the nose, or the mouth of each prototype. Results revealed that disgust was less accurately recognised than anger (Experiment 1 and 2), especially when the mouth was open (Experiment 1 and 2), and even when attention was oriented toward the distinctive features of disgust (Experiment 2). Additionally, when attention was oriented toward certain zones, the eyes (which contain characteristics of anger) had the longest dwell times, followed by the nose (which contains characteristics of disgust; Experiment 2). Thus, although participants may attend to the distinguishing features of disgust and anger, these may not aid them in accurately recognising each prototype.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".