Age and Beauty are in the Eye of the Beholder
Bibliographic record
Abstract
How "old" and "attractive" an individual appears has increasingly become an individual concern leading to the utilisation of various cosmetic surgical procedures aimed at enhancing appearance. Using eyetracking, in the present study we aimed to investigate how individuals perceive age and attractiveness of younger and older faces and what "bottom-up" facial cues are used in this process. One hundred and twenty eight digital images of neutral faces of ages ranging from 20 to 89 years were paired and presented to subjects who judged age and attractiveness levels while having their eye movements recorded. There was an effect of face attractiveness on age-rating accuracy, with attractive faces being rated younger than their true age. Similarly, stimulus age affected attractiveness ratings, with younger faces being perceived as more attractive. Judgments of age and attractiveness were tightly linked to fixations on the eye region, along with the nose and mouth. It is thus likely that cosmetic surgical procedures targeted at the eyes, nose, and mouth may be most efficacious at enhancing one's physical appearance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".