MétaCan
Menu
Back to cohort
Record W2971173070 · doi:10.1093/pch/pxz104

Strengthening the approach to oral health policy and practice in Canada

2019· article· en· W2971173070 on OpenAlexafffundabout
Shauna Hachey, Joanne Clovis, Kimberley Lamarche

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsAthabasca UniversityDalhousie University
FundersIWK Health CentreDalhousie UniversityAthabasca University
KeywordsPsychological interventionMedicineHealth policyNursingHealth careOral healthScope of practicePublic healthScope (computer science)Family medicineEconomic growth

Abstract

fetched live from OpenAlex

Evidence suggests that Canadian children from marginalized populations experience higher rates of oral diseases than their more fortunate counterparts. Oral health care in Canada is a nearly exclusively privatized and siloed system. In order to close the gap in child oral health, a combination of cohesive strategies and accessible providers is essential. The Health Impact Pyramid is a paradigm to guide health policy and programming with ready application to oral health care in Canada for the delivery of evidence-based oral health interventions with high impact. A collaborative approach among primary care providers (oral health and nonoral health), educators and the public sector, and the utilization of oral health service providers to their full scope of practice is needed to access priority populations and to deliver the most impactful interventions. Strengthening the approach to oral health care in Canada is necessary to reduce the inequities in oral health and, in turn, overall child health.

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)0.041
metaresearch head score (Gemma)0.062
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.672
Threshold uncertainty score0.779

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.062
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0270.018
Scholarly communication0.0180.005
Open science0.0080.017
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0080.001

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 head0.017
GPT teacher head0.320
Teacher spread0.302 · 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
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

Citations3
Published2019
Admission routes3
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicDental Health and Care UtilizationFrench-language works237,207