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Record W2613128933 · doi:10.1002/14651858.cd010856

Water fluoridation for the prevention of dental caries

2013· reference-entry· en· W2613128933 on OpenAlexaff
Zipporah Iheozor‐Ejiofor, Lucy A O'Malley, Anne‐Marie Glenny, Richard Macey, Rahul Alam, Peter Tugwell, Tanya Walsh, Vivian Welch, Helen V Worthington

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2013
Typereference-entry
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsWater fluoridationDentistryDental fluorosisMedicineEnvironmental healthFluoride

Abstract

fetched live from OpenAlex

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: To evaluate the effects of water fluoridation (artificial or natural) for the prevention of dental caries. To evaluate the effects of water fluoridation (artificial or natural) on dental fluorosis. The original systematic review (McDonagh 2000) included five objectives. For the purposes of the current review, the original objectives 1 to 3 will be covered by objective 1 (above). The fourth objective will be covered by objective 2 (above) and the fifth objective which explored the differential effects of natural and artificial fluoridation is not covered in the current review.

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)0.036
metaresearch head score (Gemma)0.081
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: none
Teacher disagreement score0.112
Threshold uncertainty score0.375

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.081
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0120.015
Bibliometrics0.0140.014
Science and technology studies0.0020.002
Scholarly communication0.0060.006
Open science0.0040.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.1120.012

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 head0.082
GPT teacher head0.370
Teacher spread0.288 · 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

Citations27
Published2013
Admission routes1
Has abstractyes

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