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Record W4396618494 · doi:10.59058/jaimc.v21i4.117

Comparison of Facial Angular Measurements Between Males and Females Presenting at a Tertiary Care Hospital

2024· article· en· W4396618494 on OpenAlexaff
Mehwish Nisar, Ayesha Ashraf, Shazia Ramzan, Muhammad Atif Azeem, Maimoona Batool, Farhana Ashraf

Bibliographic record

VenueJAIMC Journal of Allama Iqbal Medical College · 2024
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsCollège Montmorency
Fundersnot available
KeywordsTertiary careMedicinePsychologyFamily medicine

Abstract

fetched live from OpenAlex

Background and Objective: The effectiveness of orthodontic diagnosis and treatment planning is dependent on an accurate assessment of the patient's soft tissue profile. The objective of the study was to compare the facial angular measurements between males and females.Methods: The study comprised 100 volunteers (50 males and 50 females) ranging in age from 12 to 16 years. The respondents were chosen through convenience sampling technique from orthodontics department of children hospital Lahore. Cephalometric and photographic profile analysis was used, with angular measurements based on standard cephalometric and photographic records taken in natural head position. The study included four factors in total.Results: The mean cephalometric and photographic naso-frontal angle was 121.050 and 121.030 respectively, where as cephalometric and phographic measurement in females were 122.240 and 122.840 respectively.Conclusion: There was no significant difference in angular measurements between two genders.Keywords: Photographic analysis, Cephalometric analysis, Naso-labial angle, Naso-mental angle, Naso- frontal angle, Naso-facial angle

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.345
Teacher spread0.306 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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