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Record W2125823977 · doi:10.1177/154405910408300115

Is Fluoride Concentration in Dentin and Enamel a Good Indicator of Dental Fluorosis?

2004· article· en· W2125823977 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Dental Research · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFluoride Effects and Removal
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsDentinEnamel paintMolarFluorideDental fluorosisDentistryChemistryDental enamelPositive correlationMedicineInternal medicine

Abstract

fetched live from OpenAlex

Despite some studies correlating dental fluorosis (DF) and fluoride (F) concentration in dental enamel, no information is available about DF and dentin F concentration. Our objective was to determine the correlation between teeth F concentration and DF severity in unerupted human 3rd molars, and the correlation between dentin and enamel F concentrations in the same tooth. Ninety-nine 3rd molars were studied-53 from Fortaleza, Brazil (F water, 0.7 ppm), 22 from Toronto (1.0 ppm), and 24 from Montreal (0.2 ppm). DF severity was evaluated according to the Thylstrup-Fejerskov Index, while F concentration was analyzed by Instrumental Neutron Activation Analysis. DF severity varied between TF0 and TF4, while F concentration ranged between 39 and 550 ppm in enamel and 101 and 860 ppm in dentin. Our results showed correlation between dentin F concentration and DF (r(S) = 0.316, p = 0.001), but no correlation between enamel F concentration and DF (r(S) = 0.154, p = 0.133). No correlation was observed between dentin and enamel F concentrations in the same tooth (r(S) = 0.064, p = 0.536).

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.

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)0.000
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 score0.129
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.325
Teacher spread0.304 · 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