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Surface Anatomy of the Face in Down's Syndrome: Anthropometric Proportion Indices in the Craniofacial Regions

2001· article· en· W2080583965 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Craniofacial Surgery · 2001
Typearticle
Languageen
FieldDentistry
TopicOrthodontics and Dentofacial Orthopedics
Canadian institutionsSunnybrook Health Science CentreHospital for Sick Children
Fundersnot available
KeywordsMedicineAnthropometryCraniofacialOrthodonticsDemographyInternal medicine

Abstract

fetched live from OpenAlex

The objective of the study was to identify the proportions closest to normal and those indicating mild-to-moderate and severe degrees of disproportion. Eight proportion indices were analyzed in five craniofacial regions of 125 Down's syndrome patients, based on a total of 985 data points. More than two thirds of the patients fell within the normal range, although more than one quarter were abnormal (disproportionate). All statistical summaries were based on z-scores (adjusting for age and sex differences), converted into descriptive anthropometric categories to yield a simplified frequency distribution for each proportion index. Normal proportions were harmonious in 55.9% of patients. Disproportions were mild to moderate in 66.4%, severe in 33.6%. The highest frequency of harmony was found in the head (70.2%), the lowest in the orbits (40.8%). The highest percentage of mild-moderate disproportion was found in the face (79.3%). The highest percentage of severe disproportions was recorded in the intercanthal index of the orbits (44.7%) and the smallest frequency in the face (20.7%). In the five craniofacial regions among the normal proportions, harmonies were more frequent than disharmonies. Among the disproportions, the percentage of mild-moderate ones was greater than those of severe degree.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.312
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it