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Record W4389751101 · doi:10.1177/0272989x231214791

Reporting Economic Evaluations with Value of Information Analyses Using the CHEERS Value of Information (CHEERS-VOI) Reporting Guideline

2023· letter· en· W4389751101 on OpenAlexaff
Natalia Kunst, Annisa Siu, Michael Drummond, Sabine Grimm, Janneke P.C. Grutters, Don Husereau, Hendrik Koffijberg, Claire Rothery, Ed Wilson, Anna Heath

Bibliographic record

VenueMedical Decision Making · 2023
Typeletter
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of TorontoSickKids FoundationInstitute of Health EconomicsUniversity of OttawaPublic Health OntarioHospital for Sick Children
Fundersnot available
KeywordsGuidelineValue (mathematics)Value of informationActuarial scienceEconomic evaluationMedicineAccountingBusinessEconomicsStatisticsMathematics

Abstract

fetched live from OpenAlex

Contains fulltext : 303448.pdf (Publisher’s version ) (Open Access)

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.093
metaresearch head score (Gemma)0.158
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.544
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0930.158
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.451
GPT teacher head0.535
Teacher spread0.084 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
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

Citations1
Published2023
Admission routes1
Has abstractyes

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