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Record W3203907898 · doi:10.1016/j.identj.2021.08.052

General Dentists’ Perceptions About Their Relationship With Specialists

2021· article· en· W3203907898 on OpenAlexaffabout
Harpinder Kaur, Sonica Singhal, Michael Glogauer, Amir Azarpazhooh, Carlos Quiñonez

Bibliographic record

VenueInternational Dental Journal · 2021
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsPublic Health OntarioUniversity of TorontoToronto Public Health
Fundersnot available
KeywordsMedicinePerceptionFamily medicineDentistryPsychology

Abstract

fetched live from OpenAlex

INTRODUCTION: This paper assesses the nature of the general dentist-specialist relationship, as perceived by general dentists in Canada. METHODS: A cross-sectional web-based survey was administered to general dentists across Canada who are part of the Canadian Dental Association register and who have consented to receiving email surveys (N ≈ 11,300). Information including sociodemographic and practitioner- and practice-related factors was collected using a 47-item questionnaire. The general dentist-specialist relationship was conceptualised on the basis of 4 factors: communication, confidence, competition, and referrals. Descriptive analysis was conducted. RESULTS: The response rate for the survey was 11.7% (n = 1328). Most general dentists specified that specialists sent timely information/reports (93%), were partners in delivering care (64%), presented little competitive pressure (87%), and were strongly collegial (85%). CONCLUSIONS: In general, the study demonstrated that Canadian general dentists held a positive perception of their relationship with the specialists.

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 categoriesScience and technology studies, Insufficient 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 score0.045
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
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0210.002

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 head0.086
GPT teacher head0.494
Teacher spread0.408 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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