MétaCan
Menu
Back to cohort
Record W187225822

Clinical efficacy of a new tooth whitening dentifrice.

2002· article· en· W187225822 on OpenAlexaffabout
Farid Ayad, Amal Khalaf, Patricia Chaknis, M E Petrone, William DeVizio, A R Volpe, Howard M. Proskin

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldDentistry
TopicDental Erosion and Treatment
Canadian institutionsGeneral Electric (Canada)
Fundersnot available
KeywordsDentifriceDentistryToothbrushMedicineToothpasteStainTooth whiteningEveningOrthodonticsTooth discolorationBrushChemistryFluorideStaining
DOInot available

Abstract

fetched live from OpenAlex

The objective of this double-blind clinical study was to investigate the tooth whitening efficacy of a variation in formula of a commercially available dentifrice (Colgate Total Toothpaste). The variation (Colgate Total Plus Whitening Toothpaste) was the addition of high cleaning silica to the existing formulation. Following a baseline examination for extrinsic tooth stain, qualifying adult male and female subjects from the Mississauga, Ontario, Canada area were randomized into two treatment groups which were balanced for gender, age and level of extrinsic tooth stain. Subjects were instructed to brush their teeth twice daily (morning and evening) for one minute with their assigned dentifrice, using a soft-bristled toothbrush. Examinations for extrinsic tooth stain were repeated after six weeks' use of the study dentifrices. Ninety-three (93) subjects complied with the protocol and completed the entire study. At the six-week examination, subjects assigned to the new dentifrice formulation group exhibited statistically significantly lower levels of extrinsic tooth stain area and extrinsic tooth stain intensity than did those subjects assigned to the Colgate Total Toothpaste group.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.097
GPT teacher head0.314
Teacher spread0.217 · 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 designNon-randomized trial
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

Citations10
Published2002
Admission routes2
Has abstractyes

Explore more

Same venuePubMedSame topicDental Erosion and TreatmentFrench-language works237,207