MétaCan
Menu
Back to cohort
Record W2009292362 · doi:10.9738/intsurg-d-13-00089.1

Analysis of Potential Oral Cleft Risk Factors in the Kosovo Population

2014· article· en· W2009292362 on OpenAlexaff
Sami Salihu, Blerim Krasniqi, Osman Sejfija, Nijazi Heta, Nderim Salihaj, Agreta Geci, Milaim Sejdini, Hysni M Arifi, Ramazan Isufi, Brett A. Ueeck

Bibliographic record

VenueInternational Surgery · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsMedicineOdds ratioPregnancyConfidence intervalRisk factorHeredityOffspringPopulationLogistic regressionCase-control studyObstetricsFamily historyPediatricsDemographyInternal medicineEnvironmental healthGenetics

Abstract

fetched live from OpenAlex

The aim of this study was to analyze the association of potential risk factors such as positive family cleft history, smoking, use of drugs during pregnancy, and parental age with oral clefts in offspring within the Kosovo population. We conducted a population-based case-control study of live births in Kosovo from 1996 to 2005. Using a logistic regression model, 244 oral cleft cases were compared with 488 controls. We have excluded all syndromic clefts. Heredity increases the risk of clefts in newborns [odds ratio (OR) = 8.25, 95% confidence interval (CI) 3.12-23.52]. Clefts were also associated with smoking (OR = 1.87, 95% CI 0.75-4.08), use of drugs during pregnancy (OR = 2.25, 95% CI 0.82-5.12), increasing maternal age (OR = 1.83, 95% CI 1.42-2.49), and increasing paternal age (OR = 1.3, 95% CI 1.2- 1.4). We found heredity to be the most important factor for cleft occurrence in Kosovar newborns. Another significant potential risk factor for occurrence of clefts is the parental age. We found the use of drugs and smoking during pregnancy to be less significant.

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 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)0.000
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 score0.003
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.018
GPT teacher head0.296
Teacher spread0.278 · 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 teacher head, 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

Citations15
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueInternational SurgerySame topicCleft Lip and Palate ResearchFrench-language works237,207