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Record W4389086456 · doi:10.1016/j.esmorw.2023.10.001

ESMO Guidance for Reporting Oncology real-World evidence (GROW)

2023· article· en· W4389086456 on OpenAlexaff
Luís Castelo-Branco, Anna Pellat, Diogo Martins-Branco, Antonios Valachis, Jeroen W. G. Derksen, Karijn P.M. Suijkerbuijk, Urania Dafni, Tereza Dellaporta, Arndt Vogel, Arsela Prelaj, Rolf H. H. Groenwold, Henrique Martins, Rolf A. Stahel, Judith M. Bliss, Jakob Nikolas Kather, Nuria Ribelles, Francesco Perrone, Peter S Hall, Rodrigo Dienstmann, Christopher M. Booth, George Pentheroudakis, Suzette Delaloge, Miriam Koopman

Bibliographic record

VenueESMO Real World Data and Digital Oncology · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsPrincess Margaret Cancer CentreToronto General HospitalUniversity of TorontoQueen's UniversityUniversity Health Network
FundersEuropean Society for Medical Oncology
KeywordsReal world evidenceMultidisciplinary approachExpert opinionMedicineKey (lock)Medical educationOncologyPolitical scienceInternal medicineComputer scienceIntensive care medicine

Abstract

fetched live from OpenAlex

•Real-world evidence in oncology is evolving rapidly with many particularities.•This guidance provides key recommendations for reporting real-world evidence studies in oncology.•Recommendations are based on a review of current evidence and the authors' collective expert opinion.•Authors are a multidisciplinary group of experts from different institutions and countries.•Guidance is provided for full article development, including title, introduction, methods, results, discussion, conclusion.

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)0.023
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.616
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.671
GPT teacher head0.548
Teacher spread0.123 · 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 teacher head, not a consensus.

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

Citations25
Published2023
Admission routes1
Has abstractyes

Explore more

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