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Record W2104463247 · doi:10.1258/135763306778682341

The role of law and policy in tele-monitoring

2006· article· en· W2104463247 on OpenAlexaff
Rajen Akalu, Peter G. Rossos, Christopher T. Chan

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2006
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsToronto General HospitalUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)BusinessPublic relationsPolitical scienceInternet privacyComputer securityComputer scienceGeography

Abstract

fetched live from OpenAlex

This commentary examines the impact and limitations of existing legal policy as it relates to tele-monitoring, and considers the extent to which it serves to promote or impede remote monitoring technologies in the context of chronic illness.

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)0.077
metaresearch head score (Gemma)0.195
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.077
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.195
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0170.060
Scholarly communication0.0260.030
Open science0.0080.009
Research integrity0.0750.056
Insufficient payload (model declined to judge)0.0050.001

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 head0.012
GPT teacher head0.331
Teacher spread0.319 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

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