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Record W2342146675 · doi:10.1155/2016/9454506

The Expert Patient and Chronic Respiratory Diseases

2016· article· en· W2342146675 on OpenAlexaff
Louis‐Philippe Boulet

Bibliographic record

VenueCanadian Respiratory Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineHealth careHealth professionalsMEDLINENursingKnowledge management

Abstract

fetched live from OpenAlex

The concept of "expert patient" has been developed in the last two decades to define a patient who has a significant knowledge of his/her disease and treatment in addition to self-management skills. However, this concept has evolved over the last years, and these patients are now considered, not only to be more efficient in the management of their own condition and communicating effectively with health professionals, but to also act as educators for other patients and as resources for the last, provide feedback on care delivery, and be involved in the production and implementation of practice guidelines, as well as in the development and conduct of research initiatives. There are some barriers, however, to the integration of this new contributor to the health care team, and specific requirements need to be considered for an individual to be considered as an expert. This new player has, however, a potentially important role to improve current care, particularly in respiratory health.

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)0.005
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0140.001

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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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
GenreOther

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

Citations45
Published2016
Admission routes1
Has abstractyes

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