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Record W3155958504 · doi:10.1002/jdd.12614

Should dental schools adopt teledentistry in their curricula? Two viewpoints

2021· article· en· W3155958504 on OpenAlexaff
Maryam Amin, Jim Yuan Lai, Paul A. Lindauer, Karen McPherson, Hiba Qari

Bibliographic record

VenueJournal of Dental Education · 2021
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsCurriculumGovernment (linguistics)MedicineMedical educationNursingBusinessPublic relationsPolitical sciencePsychologyPedagogy

Abstract

fetched live from OpenAlex

INTRODUCTION: Teledentistry is a cutting edge technology that could be used to improve access to care to underserved populations and those in remote areas. OBJECTIVES: To discuss the advantages and disadvantages of adopting teledentistry into the predoctoral dental curriculum. METHODS: Two teams of dentists reviewed the pros and cons of introducing teledentistry into the predoctoral dental curriculum. RESULTS: Viewpoint 1 produced evidence that teledentistry is a cutting-edge technology that can improve access to care for underserved populations in a practical, cost-effective manner. Viewpoint 2 showed evidence that teledentistry is too new to have an evidence base to support its widespread use, legal and regulatory requirements have not been established and there is no precedent for third party payers to reimburse for this service. CONCLUSION: The authors feel that a national teledentistry policy should be developed starting at the state level with stakeholders from the dental profession, dental education, government, patient advocates, and third party payers working together to determine the best way forward.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.396
Teacher spread0.361 · 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; both teacher heads agree on what is shown here.

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

Citations27
Published2021
Admission routes1
Has abstractyes

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