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Record W2038884630 · doi:10.4103/0972-0707.87210

Caries-risk assessment with a chairside optical spectroscopic sensor by monitoring bacterial-mediated acidogenic-profile of saliva in children

2011· article· en· W2038884630 on OpenAlexaff
Anil Kishen, Annie Shrestha, Jayshree Hegde, M. Tahir, Amir Azarpazhooh

Bibliographic record

VenueJournal of Conservative Dentistry · 2011
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSalivaAcidogenesisDentistryMedicineMaterials scienceChemistryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: This study aimed to evaluate the ability of an optical spectroscopic sensor (OSS) to monitor bacterial-mediated acidogenic-profile of saliva resulting from bacteria-sucrose interaction. MATERIALS AND METHODS: Stage-1, characterization experiments were conducted to standardize the OSS. Stage-2 clinical experiments were carried out on stimulated saliva samples from 70 children of age-group 1-12 years. The bacterial-mediated acidogenic-profile of saliva mixed with sucrose was monitored using the OSS for 180 minutes. RESULTS: The clinical patients were categorized based on the dmfs score as caries-active, caries-inactive and caries-free. The bacterial-mediated acidogenic-profile measured in terms of t1/2 monitored using the OSS was significantly different between the caries-free and caries-active (P<0.05); and caries-free and caries-inactive groups (P<0.005). CONCLUSIONS: The significant correlation of the acidogenic-profile determined using the OSS and the caries-status highlighted the OSS as a sensitive and rapid chairside tool for the quantification of the acidogenic-profile of saliva that could help in monitoring the caries-risk in children.

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 score0.091
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.294
Teacher spread0.274 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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