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Record W7132922685

Asthma as a risk factor for dental caries and dental erosion in children and adolescents

2007· dissertation· W7132922685 on OpenAlexfundaboutno aff
Geneviève Abi-Nahed

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldDentistry
TopicDental Erosion and Treatment
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsAsthmaRisk factorRelative riskAssociation (psychology)Dental decayOral healthDental healthBehavioral Risk Factor Surveillance System
DOInot available

Abstract

fetched live from OpenAlex

Objectives. The objective is to look at the association between asthma and oral health by attempting to answer the following question: is asthma a risk factor for dental decay and/or dental erosion in children and adolescents via an evidence based report (EBR) and an analysis of a national data base set. Methods. For the EBR, a total of 8 studies were identified for decay and 3 for erosion. For the database analysis report, data was analyzed from the 2003 Canadian Community Health Survey public use data file. Results. In the EBR, two studies revealed a positive association between asthma and decay vs. only one with erosion. The database analysis report demonstrated a higher percentage of tooth sensitivity in asthmatic children with asthma. Conclusion. Since no clear association between asthmatic children, decay and erosion could be established, education and prevention programs should be directed to this group until an association can be proven.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.010
GPT teacher head0.334
Teacher spread0.324 · 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

Citations0
Published2007
Admission routes2
Has abstractyes

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