MétaCan
Menu
Back to cohort
Record W2081270036 · doi:10.1007/s10198-013-0471-6

Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement

2013· article· en· W2081270036 on OpenAlexaff
Don Husereau, Michael Drummond, Stavros Petrou, Chris Carswell, David Moher, Dan Greenberg, Federico Augustovski, Andrew Briggs, Josephine Mauskopf, Elizabeth Loder

Bibliographic record

VenueThe European Journal of Health Economics · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsOttawa HospitalInstitute of Health Economics
Fundersnot available
KeywordsChecklistGovernment (linguistics)Statement (logic)Delphi methodConsolidated Standards of Reporting TrialsSystematic reviewEconomic evaluationPsychological interventionPublic relationsDelphiPolitical scienceMEDLINEMedicineMedical educationPsychologyNursingComputer scienceLaw

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)0.272
metaresearch head score (Gemma)0.609
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.728
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2720.609
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0160.024
Science and technology studies0.0020.005
Scholarly communication0.0120.005
Open science0.0080.007
Research integrity0.0120.020
Insufficient payload (model declined to judge)0.0140.010

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 head0.447
GPT teacher head0.480
Teacher spread0.033 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations236
Published2013
Admission routes1
Has abstractno

Explore more

Same venueThe European Journal of Health EconomicsSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207