MétaCan
Menu
Back to cohort
Record W4400222791 · doi:10.15517/ijds.2024.60813

Scientometric Analysis of Activated Carbon or Probiotics in Mouthwashes or Toothpastes: Dynamicity, Spatiotemporal Evolution and Trends

2024· article· en· W4400222791 on OpenAlexaboutno aff
Franco Mauricio, Cesar Mauricio‐Vilchez, Diego Galarza-Valencia, Daniel Alvítez-Temoche, Luzmila Vilchez, Fran Espinoza‐Carhuancho, Frank Mayta‐Tovalino

Bibliographic record

VenueOdovtos - International Journal of Dental Sciences · 2024
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsFood scienceChemistry

Abstract

fetched live from OpenAlex

The use of activated charcoal and probiotics is a controversial topic nowadays due to their potential oral health benefits. Thus, the aim of this research was to perform a scientometric analysis of activated charcoal or probiotics in mouthwashes or dentifrices by means of dynamicity, spatiotemporal evolution, and trends. A study was carried out to look back at scientific publications between 2005 and 2022 using the Web of Science. To analyze the data, various bibliometric indicators were used. The process of retrieving information was completed on July 28, 2023. It was found that only 1 article was published in 1990. Furthermore, the highest co-citation occurred in cluster 9 (Dentistry, Dermatology, Surgery), indicating a higher relevance and frequency with cluster 8 (Molecular Biology, Genetics). In the cluster view, 15 large clusters were identified, with cluster 0 (Activated Carbon) being the largest and occupying the greatest centrality. On the other hand, the cross-country collaboration map showed active collaborations between Australia and New Zealand, Brazil, and Canada. We found a significant growth of scientific publications on probiotics and activated charcoal in the field of dentistry and related disciplines between 1990 and 2023.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.103
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.009
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.050
GPT teacher head0.403
Teacher spread0.353 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueOdovtos - International Journal of Dental SciencesSame topicDental Research and COVID-19CategoryBibliometricsFrench-language works237,207