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Record W2888793209 · doi:10.1016/s1470-2045(18)30418-2

Statistical analysis of patient-reported outcome data in randomised controlled trials of locally advanced and metastatic breast cancer: a systematic review

2018· review· en· W2888793209 on OpenAlexaff
Madeline Pe, Lien Dorme, Corneel Coens, Ethan Basch, Melanie Calvert, Alicyn Campbell, Charles S. Cleeland, Kim Cocks, Laurence Collette, Linda Dirven, Amylou C. Dueck, Nancy Devlin, Hans‐Henning Flechtner, Carolyn Gotay, Ingolf Griebsch, Mogens Grøenvold, Madeleine King, Michael Koller, Daniel C. Malone, Francesca Martinelli, Sandra A. Mitchell, Jammbe Musoro, Kathy Oliver, Elisabeth Piault‐Louis, Martine Piccart, Francisco Pimentel, Chantal Quinten, Jaap C. Reijneveld, Jeff A. Sloan, Galina Velikova, Andrew Bottomley

Bibliographic record

VenueThe Lancet Oncology · 2018
Typereview
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of British Columbia
FundersEuropean Organisation for Research and Treatment of CancerBoehringer Ingelheim
KeywordsMedicineBreast cancerRandomized controlled trialSample size determinationMEDLINESystematic reviewClinical trialQuality of life (healthcare)Meta-analysisMissing dataData qualityMedical physicsAlternative medicineCancerFamily medicineInternal medicinePathologyStatistics

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 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)0.011
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.661
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0390.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.232
GPT teacher head0.521
Teacher spread0.289 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations99
Published2018
Admission routes1
Has abstractno

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