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Record W4415586605 · doi:10.21083/crrf.v29i1.7734

Teledermatology: Connecting Specialists to Rural BC

2025· article· W4415586605 on OpenAlexaffabout
Rebecca Afford

Bibliographic record

VenueProceedings of the Canadian Rural Revitalization Foundation · 2025
Typearticle
Language
FieldVeterinary
TopicInfectious Diseases and Mycology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTelehealthTelemedicineHealth careRural areaPrimary careRural healthPrimary health careValue (mathematics)

Abstract

fetched live from OpenAlex

Advancements in as well as patient and care provider amelioration with telehealth has made healthcare more accessible for those living in rural and remote areas. Often burdened by cost, geography, physical ability, weather, and availability of physicians, people living outside larger centers can have difficulty accessing the care they need. The Canadian Health Act states that"the primary objective of Canadian health care policy is to protect, promote and restore the physical and mental well-being of residents of Canada and to facilitate reasonable access to health services without financial or other barriers", but many of these barriers still exists for many Canadians. Currently, telemedicine initiatives are taking place in British Columbia and have been well-received by both patients and healthcare providers. Inspired by such initiatives and the sparse and selective distribution of dermatologists in the province, implementing a novel technology-based platform is needed to provide "reasonable access" to dermatologists in underserviced areas. Currently, the use of telehealth for dermatology is not prevalent in common practice. Through speaking to primary care physicians working in northern and rural locations about their attitudes toward telehealth, we are hoping to understand the obstacles hindering the use of this technology in hopes to create a user-focused platform. In time, a "teledermatology" program could be of economic value and will ensure patient safety by providing more expedient access to care as well as reducing the harms associated with travel. As this technology progresses, telehealth will become commonplace in providing equitable healthcare for Canadians.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.291
Teacher spread0.277 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2025
Admission routes2
Has abstractyes

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Same venueProceedings of the Canadian Rural Revitalization FoundationSame topicInfectious Diseases and MycologyFrench-language works237,207