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Record W4381033167 · doi:10.1016/j.jobcr.2023.05.011

Physical and chemical properties of saliva and its role in Early Childhood caries – A systematic review and meta-analysis

2023· review· en· W4381033167 on OpenAlexaboutno aff
Dhanalakshmi Ravikumar, Pratibha Ramani, R. Gayathri, K Hemashree, Pranitha Prabhakaran

Bibliographic record

VenueJournal of Oral Biology and Craniofacial Research · 2023
Typereview
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineObservational studySalivaEarly childhood cariesEtiologyMEDLINEEarly childhoodPediatricsDentistryOral healthPsychologyDevelopmental psychologyPsychiatryPathologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Early Childhood Caries is a chronic disease of childhood and salivary parameters are considered as one of the prime etiological factors of Early Childhood Caries. Aim: To develop a systematic review based on the relation between physical and chemical properties of saliva and Early childhood caries by comparing children with and without Early childhood caries. Methods: PubMed, Cochrane, Lilacs, Embase, Scopus, and additional manual search was done up to April 2021 to identify the original cross-sectional observational studies published in English. The risk of bias and quality of the included papers were assessed based on New castle Ottawa guidelines. Results: From a total of 1709 identified studies, only 22 articles were included in this systematic review and 10 studies were qualified for meta-analysis. Eight studies were classified as ''moderate risk of bias'' and fourteen studies were classified as ''high risk of bias''. Conclusion: There was a significant difference in physical and chemical properties of saliva in children with and without Early childhood caries. Since wide disparity were evident in available studies, further studies are needed to arrive to a definitive conclusion.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.838
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
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 head0.192
GPT teacher head0.463
Teacher spread0.271 · 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 designSystematic review
Domainnot available
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

Citations19
Published2023
Admission routes1
Has abstractyes

Explore more

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