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Record W2119358111 · doi:10.5539/gjhs.v6n7p66

Prevalence of Different Kinds of Maxillofacial Fractures and Their Associated Factors Are Surveyed in Patients

2014· article· en· W2119358111 on OpenAlex
Hanane Latifi

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFalling (accident)Observational studyDentistryEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Nowadays maxillofacial fractures have increased. In this study prevalence of different kinds of maxillofacial fractures and their associated factors are surveyed in patients referred to Imam Khomeini Hospital, Urmia in 2011. METHODS: The study was across-sectional observational study. 637 cases of patients with a confirmed diagnosis of maxillofacial fractures in 2011 referred to Imam Khomeini Hospital, Urmia and their data records were analyzed using SPSS software and chi-square tests. RESULTS: In this study, 457 patients were male and 178 were female and the mean age was 14.47 ± 26.68 years. Falling was the most common cause of fractures after accidents and assaults were the most common causes. The most common site of nasal fractures was about 66.4% and then fractures in several places about 14.9% and mandibular 7.1%. CONCLUSION: Based on the results obtained in the present study with other studies in this area it is concluded that maxillofacial fractures in males and in 20 to 30 years of age is prevalent and is mostly due to falling and road accidents and are further seen in nasal bone and mandible.

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)0.001
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 score0.019
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.305
Teacher spread0.285 · 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