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Record W2041157748 · doi:10.1016/j.sdentj.2013.04.001

Severity and causality of maxillofacial trauma in the Southern region of Saudi Arabia

2013· article· en· W2041157748 on OpenAlexaff
Mazen Almasri

Bibliographic record

VenueThe Saudi Dental Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsMcGill University
FundersKing Khalid UniversityKing Abdulaziz University
KeywordsMedicineTertiary careRoad trafficCausality (physics)Trauma careMajor traumaOccupational safety and healthEmergency medicineMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to examine the causality and severity of maxillofacial trauma (MFT) among patients referred to a tertiary heath care center in the Southern Aseer region of Saudi Arabia. MATERIALS AND METHODS: The charts of all MFT patients referred to the tertiary care center from September 2010 to November 2011 were retrospectively reviewed. Pertinent data, including patient age, gender, and cause of injury, were obtained from 101 selected charts. RESULTS: Male patients comprised 91% of the 101 selected cases. The highest percentage of MFT cases (88.7%) were caused by road traffic accidents (RTAs) while physical altercations and sports injuries accounted for approximately 6% and 2.8% of MFT cases, respectively. A high fracture: patient ratio of 2.4:1 was observed, which was likely due to vehicular speeding (high energy trauma) involved in RTAs in the mountain regions. CONCLUSION: RTAs are a major cause of MFT in the southern region of Saudi. These accidents cause a heavy burden on the health care sector.

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)0.002
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.261
Teacher spread0.238 · 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

Citations38
Published2013
Admission routes1
Has abstractyes

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