MétaCan
Menu
Back to cohort
Record W2051594243 · doi:10.1177/1357633x0501100807

User satisfaction with a telemedicine amputee clinic in Saskatchewan

2005· article· en· W2051594243 on OpenAlexaffabout
Gary Linassi, R Li Pi Shan

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2005
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTelemedicineSession (web analytics)Patient satisfactionVideoconferencingTelehealthMedical emergencyMedicineUser satisfactionMultimediaNursingComputer scienceHealth careWorld Wide WebHuman–computer interaction

Abstract

fetched live from OpenAlex

A group of 15 patients with amputee-related diagnoses were given a satisfaction survey after telemedicine assessment. Most of the videoconferencing sessions used an IP connection at 768 kbit/s. The patients were seen at four sites. The average connection time was less than 5 min and the average time for a session was approximately 40 min. Thirteen questions required scaled responses (poor, fair, good, excellent) and two required yes/no answers. The 13 categories broadly related to satisfaction with the telemedicine service and the quality of specialist care. In all categories, 97% of the responses fell in the good to excellent range. Concerns were raised about ease of access to local telemedicine sites, connection waiting times and lack of familiarity with telemedicine technology. The study showed that telemedicine was acceptable to patients with amputations and provided a reliable assessment of the amputee.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.326
Teacher spread0.310 · 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

Citations19
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Telemedicine and TelecareSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207