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Record W3038614642 · doi:10.1177/2380084420941777

COVID-19 Has Clarified 2 Foundational Policy Questions in Dentistry

2020· article· en· W3038614642 on OpenAlexaff
Carlos Quiñonez, Marko Vujicic

Bibliographic record

VenueJDR Clinical & Translational Research · 2020
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Context (archaeology)Dental carePoliticsHealth carePolitical scienceOral healthPublic relationsStatement (logic)Oral health care2019-20 coronavirus outbreakSociologyMedicineLawDentistryHistoryPathology

Abstract

fetched live from OpenAlex

Before the COVID-19 pandemic, health policy debates about the importance of oral health and dental care were intensifying around the world. These debates were invariably complex and muddled by political, professional, and commercial interests. Although, in broad terms, 2 foundational questions have tended to undergird debates on how dental care should be addressed in health policy. These are: who should receive the support of governments, and what constitutes essential or medically necessary dental care? In our view, the COVID-19 pandemic has provided a stark social and policy context that has radically clarified both questions. Knowledge Transfer Statement: This commentary can be used by governments, regulators, professional groups, and other stakeholders in their considerations of what constitutes essential or medically necessary dental care and how to best allocate dental care resources.

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)0.084
metaresearch head score (Gemma)0.124
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.099
Threshold uncertainty score0.444

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.124
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.003
Science and technology studies0.0180.036
Scholarly communication0.0220.016
Open science0.0070.013
Research integrity0.0990.078
Insufficient payload (model declined to judge)0.0090.002

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 head0.542
GPT teacher head0.611
Teacher spread0.069 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations17
Published2020
Admission routes1
Has abstractyes

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