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Elders assessment of an evolving model of oral health

2007· article· en· W2095498855 on OpenAlexaff
Mario Brondani, S. Ross Bryant, Michael I. MacEntee

Bibliographic record

VenueGerodontology · 2007
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineRelevance (law)Oral healthFocus groupNarrativeQualitative researchGerontologyFamily medicineSocial science

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate qualitatively a model of oral health through focus groups among elders. METHODS: The participants (30 women and 12 men; mean age: 75 years) attended one of six focus groups to discuss the relevance of the model to their oral health-related beliefs and experiences, and transcripts of the narratives were analysed systematically for the components, associations and recommendations emerging from the discussions. RESULTS: The groups confirmed the relevance of the original components of the model with minor modifications, but felt that for completeness it required four additional components: diet; economic priorities; personal expectations; and health values and beliefs. They recommended that the negative connotations of limited activity, impairment and restricted participation were modified with the positive terms activity and participation, and they suggested that ellipses rather than concentric circles more aptly illustrate the dynamic and overlapping importance of the various components in the model. CONCLUSION: The original model required additional components and graphic representation to accommodate all of the experiences and beliefs relating to the oral health of the elders who participated in this qualitative study.

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)0.015
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.413
Teacher spread0.356 · 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 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

Citations56
Published2007
Admission routes1
Has abstractyes

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