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Association of human papillomavirus with denture wearing

2011· article· en· W1605309829 on OpenAlexaff
Rajan Saini, Nurainina Binti Osman, Mazian Ismail, Farini Mohd Sobri, Thean‐Hock Tang, Jacinta Santhanam

Bibliographic record

VenueJournal of Investigative and Clinical Dentistry · 2011
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsBC Cancer Agency
FundersDeutsches Krebsforschungszentrum
KeywordsOdds ratioMedicineHuman papillomavirusDentistryConfidence intervalPolymerase chain reactionRisk factorOral hygieneOral cavityInternal medicineBiologyGeneGenetics

Abstract

fetched live from OpenAlex

AIM: To determine the prevalence of human papillomavirus in the oral cavity of denture wearers. METHODS: Swabs were collected from 72 denture wearers and 72 controls (non-denture wearers) to obtain DNA. Amplification of the β-globin gene was performed by polymerase chain reaction to check the integrity of extracted DNA. The presence of human papillomavirus in the DNA sample was detected by nested polymerase chain reaction. RESULTS: The prevalence of human papillomavirus was found to be significantly higher in the oral cavity of denture wearers (38/72, 52.8%) than in the controls (17/72, 23.6%; odds ratio = 3.612, confidence interval = 1.771/7.385, P = <0.001). When adjusted for variables, including age, sex, ethnicity, and smoking habit, human papillomavirus was still found to be significantly associated with denture wearing, with an adjusted odds of 3.2 (P = 0.008). No association of human papillomavirus positivity was found with denture variables, including denture type, denture material type, duration of denture wearing, and denture hygiene (P > 0.05). Low-risk human papillomavirus types were found to be more frequent in both groups. CONCLUSIONS: The prevalence of human papillomavirus in the oral cavity of denture wearers was found to be significantly higher compared to controls; however, it was mainly low-risk types.

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 score0.010
Threshold uncertainty score0.195

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 head0.116
GPT teacher head0.381
Teacher spread0.265 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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