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Record W2127510188 · doi:10.1258/rsmsmj.51.3.26

Dietary and Social Characteristics of Children with Severe Tooth Decay

2006· article· en· W2127510188 on OpenAlexfundno aff
FL Cameron, LT Weaver, C M Wright, Richard Welbury

Bibliographic record

VenueScottish Medical Journal · 2006
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsMedicineUnderweightDental decayDentistryBody mass indexHabitDemographyPediatricsOral healthOverweight

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Dental decay remains a major public health problem in Scottish children. The aim of this study was to investigate the relationship between diet, bowel habit, social class, and body mass index (BMI) in children with severe tooth decay. CHILDREN AND METHODS: A cross sectional study of 165 children aged 3 -11 years attending Glasgow Dental Hospital for extraction of teeth under dental general anaesthesia (DGA), was undertaken. A structured questionnaire was used to obtain information from each child on diet, bowel habit, and social status of their parents. Fibre and sugar scores were calculated from the frequency of consumption of a range of relevant foods. RESULTS: The children (mean age 5.7 (SD1.8) years) had between 1 and 20 decayed, missing or filled primary teeth (dmft) with a mean dmft of 7.9 (SD 3.5). 37% ate a chocolate bar daily, and 29% regularly drank a sugary drink after brushing their teeth. An excess of children were from the most deprived parts of the city and they had the worst decay. Children with the worst decay were also significantly thinner. No relationship was found between tooth decay and bowel habit. CONCLUSIONS: In this selected group of children with poor dental health, those from deprived families were over-represented and had significantly more decay. Severe dental decay was also associated with underweight.

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)0.000
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 score0.234
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.008
GPT teacher head0.269
Teacher spread0.261 · 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

Citations47
Published2006
Admission routes1
Has abstractyes

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