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Record W3006044281

Telemedicine in the driver's seat: new role for primary care access in Brazil and Canada: The Besrour Papers: a series on the state of family medicine in Canada and Brazil.

2020· article· en· W3006044281 on OpenAlexaffabout
Payal Agarwal, Natasha Kithulegoda, Roberto Nunes Umpierre, John Pawlovich, Juliana Nunes Pfeil, Otávio Pereira D’Ávila, Marcelo Goncalves, Erno Harzheim, David Ponka

Bibliographic record

VenuePubMed · 2020
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsCollege of Family Physicians of CanadaUniversity of British ColumbiaWomen's College Hospital
Fundersnot available
KeywordsTelemedicineExpansiveHealth careMedicineScale (ratio)Political scienceGeographyLawCartography
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To contrast how Brazil's and Canada's different jurisdictional and judicial realities have led to different types of telemedicine and how further scale and improvement can be achieved. COMPOSITION OF THE COMMITTEE: A subgroup of the Besrour Centre of the College of Family Physicians of Canada and Canadian telemedicine experts developed connections with colleagues in Porto Alegre, Brazil, and collaborated to undertake a between-country comparison of their respective telemedicine programs. METHODS: Following a literature review, the authors collectively reflected on their experiences in an attempt to explore the past and current state of telemedicine in Canada and Brazil. REPORT: Both Brazil and Canada share expansive geographies, creating substantial barriers to health for rural patients. Telemedicine is an important part of a universal health system. Both countries have achieved telemedicine programs that have scaled up across large regions and are showing important effects on health care costs and outcomes. However, each system is unique in design and implementation and faces unique challenges for further scale and improvement. Addressing regional differences, the normalization of telemedicine, and potential alignment of telemedicine and artificial intelligence technologies for health care are seen as promising approaches to scaling up and improving telemedicine in both countries.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.280
Teacher spread0.249 · 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 teacher head, 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

Citations21
Published2020
Admission routes2
Has abstractyes

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