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Record W1993086930 · doi:10.1159/000261637

Distribution of Sucrose around the Mouth and Its Clearance after a Sucrose Mouthrinse or Consumption of Three Different Foods

2009· article· en· W1993086930 on OpenAlexaff
L.M.D. Macpherson, C. Dawes

Bibliographic record

VenueCaries Research · 2009
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSucroseSalivaDentistryTooth surfaceMolarSugarSugar consumptionMouth rinseChemistryDental plaqueOral hygieneFood scienceOrthodonticsMedicineBiochemistry

Abstract

fetched live from OpenAlex

The distribution of sucrose in whole saliva and in saliva from seven different regions of the mouth was determined in 10 subjects over the 10-min period following the chewing of a doughnut, sucking on a mint candy, the drinking of orange juice, or use of a 10% sucrose mouthrinse. With all products, the sucrose was distributed non-uniformly, with particularly low concentrations on the lingual surfaces of the lower incisors and the facial surfaces of the upper molars. Clearance was also most rapid from these sites. Since the depth and duration of a Stephan curve in dental plaque is influenced by the sugar concentration to which the plaque is exposed, the results, together with previous results on salivary film velocity in different regions of the mouth, help to provide an explanation for the site-specificity of smooth-surface caries and of supragingival calculus deposition.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.098
GPT teacher head0.383
Teacher spread0.285 · 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 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

Citations21
Published2009
Admission routes1
Has abstractyes

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