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Record W2896124575 · doi:10.1111/cdoe.12430

Caries reporting in studies that used the International Caries Detection and Assessment System: A scoping review

2018· review· en· W2896124575 on OpenAlexafffund
Mohamed ElSalhy, Ussama Ali, Hollis Lai, Carlos Flores‐Mir, Maryam Amin

Bibliographic record

VenueCommunity Dentistry And Oral Epidemiology · 2018
Typereview
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of AlbertaGeorgian College
FundersAlberta Innovates - Health Solutions
KeywordsMedicineDentistryPermanent teethDentitionPermanent dentitionOrthodontics

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore how caries was reported in studies that employed the International Caries Detection and Assessment System (ICDAS). METHODS: A systematic database search up to August 2017 was carried out using PubMed, Ovid MEDLINE, Cochrane library and ISI Web of Science electronic databases. Only studies that used the ICDAS for dental caries examinations were included. Studies were excluded if the examination was done only for the validation or the calibration of the ICDAS and/or if the examination was not done for the whole dentition. Measures used to report caries were considered. RESULTS: A total of 126 papers met the inclusion criteria. Forty-four different synthesis measures were used to report caries. Most of the studies used a combination of multiple measures to report patient's caries level. These reporting measures cluster into four main groups: the number of individual ICDAS scores (ie, total counts of every score); the number of decayed surfaces/teeth (ie, total counts of combined caries scores for surfaces or teeth); measures of caries experience (ie, total counts of combined caries scores, filled and/or missing surfaces or teeth); and measures of central tendency and dispersion. The number of decayed surfaces and individual ICDAS scores were the most commonly used measures. Three studies used mean ICDAS score (ie, total ICDAS scores divided by the number of teeth), two used mean ICDAS score of carious teeth (ie, total ICDAS scores divided by the number of carious teeth) and two used the maximum ICDAS score (ie, highest ICDAS score recorded). The total ICDAS score was used only once. Many studies synthesized from the ICDAS the number of decayed, missing and filled teeth/surfaces (dmft/DMFT, dmfs/DMFS) as a measure of caries experience. CONCLUSIONS: There are variations among studies in the utilization of the system to summarize caries. Most studies presented caries data using the categorical characteristics of the ICDAS.

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)0.043
metaresearch head score (Gemma)0.179
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.179
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0100.011
Bibliometrics0.0470.034
Science and technology studies0.0020.002
Scholarly communication0.0070.007
Open science0.0030.004
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.405
GPT teacher head0.538
Teacher spread0.133 · 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.

Study designSystematic review
DomainReporting
GenreReview

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

Citations9
Published2018
Admission routes2
Has abstractyes

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