Age and Beauty are in the Eye of the Beholder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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