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Record W1966171264 · doi:10.1179/acb.2007.007

IMPLEMENTING AND OPTIMISING AN ELECTRONIC LIBRARY OF HEALTH CARE IN BELGIUM: RESULTS OF A PILOT STUDY

2007· article· en· W1966171264 on OpenAlexaff
Karin Hannes, Robert Vander Stichele, Emmy M C Simons, Siegfried Geens, Jo Goedhuys, Bert Aertgeerts

Bibliographic record

VenueActa Clinica Belgica · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsCochrane
Fundersnot available
KeywordsMedicineGateway (web page)Medical prescriptionHealth careMEDLINEQuality (philosophy)Medical libraryScientific evidenceMedical educationWorld Wide WebNursingComputer science

Abstract

fetched live from OpenAlex

Health care practitioners are expected to incorporate results from the best available, scientific information into their daily clinical decision-making process. Useful formats of evidence for practitioners include selected reviews, abstracts in which research results are discussed, "quick answer", evidence-based website including for example diagnostic and therapeutic algorithms, drugs prescription and non-drug therapy. An increasing amount of practitioners has access to the World Wide Web, either at home or at the office. However, easy and cheap access to objective and high quality research results is limited. Many practitioners lack the skills to efficiently navigate complicated medical databases. In 2003 an 'Electronic Library of Health Care' was introduced in Belgium. The main goal of the electronic library is to provide a gateway to scientific evidence to Belgian health care practitioners from different disciplines. This paper presents the results of a pilot project to implement the library in the field. It also describes recent developments and adjustments that increased the efficacy of this gateway to evidence.

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)0.022
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.202
GPT teacher head0.555
Teacher spread0.352 · 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.

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

Citations1
Published2007
Admission routes1
Has abstractyes

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