How deep do you go? Clinical prediction of nasopharyngeal depth based on facial measurements
Bibliographic record
Abstract
Nasopharyngeal depth (ND) prediction is clinically relevant in performing medical procedures, and in enhancing technique accuracy and patient safety. Nonetheless, clinical predictive variables and normative data in adults remain limited. This study aimed to determine normative data on ND and its correlation to external facial measurements. A multicenter cross-sectional study obtained data from adults presenting to otolaryngology clinics at five sites in Canada, Italy, and Spain. Investigators compared endoscopically measured depth from the nasal sill (soft tissue between the nasal ala and columella) to nasopharynx along the nasal floor to the "curved distance from the alar-facial groove along the face to the tragus" and "distance from the tragus to a plane perpendicular to the philtrum." When sinus computed tomography images were available, the distance from the nasopharynx to the nasal sill was also collected. 371 patients participated in the study (41% women; 51 years old, SD 18). Average ND was 9.4 cm (SD 0.86) and 10.1 cm (SD 0.9) for women and men, respectively (p < 0.001; 95% CI 0.46-0.86). Perpendicular distance was strongly correlated to ND (r = 0.775; p < 0.001), with an average underestimation of 0.1 cm (SD 0.65; 95% CI 0.06-0.2). The equation: ND (cm) = perpendicular distance*0.773 + 2.344, generated from 271 randomly selected participants, and validated on 100 participants, resulted in a 0.03 cm prediction error (SD 0.61; 95% CI -0.08-0.16). Nasopharyngeal depth can be approximated by the distance from the tragus to a plane perpendicular to the philtrum.
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".