MétaCan
Menu
Back to cohort
Record W1964725182 · doi:10.1007/s10916-014-0073-6

Assessing the Prognoses on Health Care in the Information Society 2013 - Thirteen Years After

2014· article· en· W1964725182 on OpenAlexaff
Petra Knaup, Elske Ammenwerth, Carl Dujat, Andrew Grant, Arie Hasman, Andreas Hein, Achim Hochlehnert, Casimir Kulikowski, John Mantas, Víctor Maojo, Michael Marschollek, Lincoln Moura, Maik Plischke, Rainer Röhrig, Jürgen Stausberg, Katsuhiko Takabayashi, Frank Ückert, Alfred Winter, Klaus-Hendrik Wolf, Reinhold Haux

Bibliographic record

VenueJournal of Medical Systems · 2014
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHealth informaticsHealth careInformaticsMedicineTelemedicineHealth information exchangeHealth information technologyInformation and Communications TechnologyMatching (statistics)MEDLINEInformation technologyFamily medicineHealth informationMedical emergencyNursingComputer sciencePublic healthPolitical sciencePathologyWorld Wide Web

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.004
metaresearch head score (Gemma)0.017
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.454
Teacher spread0.417 · 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
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

Citations16
Published2014
Admission routes1
Has abstractno

Explore more

Same venueJournal of Medical SystemsSame topicElectronic Health Records SystemsFrench-language works237,207