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Record W4296637517 · doi:10.1007/s40368-022-00753-3

Effect of sleep on development of early childhood caries: a systematic review

2022· review· en· W4296637517 on OpenAlexaboutno aff
Divesh Sardana, Barbara C. Galland, Benjamin J. Wheeler, Cynthia Kar Yung Yiu, Manikandan Ekambaram

Bibliographic record

VenueEuropean Archives of Paediatric Dentistry · 2022
Typereview
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
FundersUniversity of Hong KongUniversity of Otago
KeywordsMedicineEarly childhood cariesDentistrySleep (system call)PediatricsOral health

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the impact of sleep on the development of early childhood caries (ECC). METHODS: Seven electronic databases and grey literature were searched with various keyword combinations. Two reviewers independently selected studies, extracted data, and assessed the risk of bias using the Newcastle-Ottawa Scale. The studies were included if they evaluated the impact of sleep parameters on the caries experience or severity of ECC in children under 6 years of age. RESULTS: Four cross-sectional studies and two longitudinal studies were included. Children who had irregular bedtimes had a 66-71% higher chance of developing ECC. Children who slept after 11 pm might have a 74-85% higher chance of developing ECC. Children who slept less than 8 h during the night had a 30% increased risk of caries than children who slept more than 11 h. CONCLUSION: Irregular or late bedtime and fewer sleeping hours could be an independent risk factor for ECC. The risk of ECC might be related inversely in a dose-response manner to the number of sleep hours.

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)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.296
Teacher spread0.281 · 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 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

Citations20
Published2022
Admission routes1
Has abstractyes

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