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Record W4389397921 · doi:10.1680/jbibn.23.00034

Hydroxyapatite as an active ingredient in oral care: an international symposium report

2023· article· en· W4389397921 on OpenAlexaff
M Pawińska, Elżbieta Paszyńska, Hardy Limeback, Bennett T. Amaechi, Helge‐Otto Fabritius, Bernhard Ganss, Kelsey O’Hagan-Wong, Erik Schulze zur Wiesche, Frederic Meyer, Joachim Enax

Bibliographic record

VenueBioinspired Biomimetic and Nanobiomaterials · 2023
Typearticle
Languageen
FieldDentistry
TopicDental Erosion and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsActive ingredientIngredientMedicineDentistryPharmacologyPathology

Abstract

fetched live from OpenAlex

Hydroxyapatite, Ca 5 (PO 4 ) 3 (OH), is a bioinspired active ingredient for preventive oral health care. The use of hydroxyapatite in the prevention of oral diseases has gained interest, particularly in recent years. Hydroxyapatite can be used in office and for daily oral care (e.g. in toothpastes and mouthwashes). The first clinical efficacy studies on caries prevention and reduction of symptoms of dentin hypersensitivity were conducted in the 1980s. These were followed by various in vitro and in situ studies and several more recent clinical trials. A number of systematic reviews and meta-analyses on the use of hydroxyapatite in preventing oral health problems have been published. Summarizing these data, hydroxyapatite is a versatile active ingredient with multiple benefits that include caries prevention, relief from dentin hypersensitivity and tooth whitening. Since this calcium phosphate mineral has an excellent biocompatibility, it is safe for all patient groups. This interdisciplinary review gives an overview of the developments in hydroxyapatite research, highlights the research progress made regarding hydroxyapatite as a biomimetic active ingredient and summarizes the state-of-the-art evidence in support of hydroxyapatite efficacy.

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 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.001

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 head0.020
GPT teacher head0.311
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations15
Published2023
Admission routes1
Has abstractyes

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