Esthetics and smile characteristics evaluated by laypersons
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
OBJECTIVE: To collect data regarding Canadian laypersons' perceptions of smile esthetics and compare these data to US data in order to evaluate cultural differences. MATERIALS AND METHODS: Using Adobe Photoshop 7, a digital image of a posed smile of a sexually ambiguous lower face was prepared so that hard and soft tissue could be manipulated to alter buccal corridor (BC), gingival display (GD), occlusal cant (OC), maxillary midline to face discrepancy (MMFD), and lateral central gingival discrepancy (LCGD). Adult Canadian laypersons (n = 103) completed an interactive computer-based survey of 29 randomized images to compare smile preferences for these variables. The custom survey was developed to display fluid, continuously appearing modifiable smile variables using MATLAB R2008 for presentation. These data were compared with previously published data for US laypersons. Statistical inference was determined using Wilcoxon rank sum tests. RESULTS: Canadian laypersons were more sensitive in detecting deviations from ideal and had a narrower range of acceptability thresholds for BC, GD, OC, MMFD, and LCGD. Ideal esthetic values were significantly different only for BC. CONCLUSIONS: It appears that cultural differences do exist related to smile characteristics. Clinically significant differences in the preference of the smile characteristics were found between Canadian and US laypersons. Canadian laypersons, on average, were more discriminating to deviations from ideal and had a narrower range of acceptability.
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 | 0.001 | 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) | 0.001 | 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