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Record W3028527898 · doi:10.1016/j.annonc.2020.03.245

144P Patient-reported outcomes (PROs) in advanced breast cancer (ABC) treated with ribociclib (RIB) + fulvestrant (FUL) as first-line (1L) and second-line (2L) therapy in MONALEESA-3 (ML-3)

2020· article· en· W3028527898 on OpenAlexafffund
Peter A. Fasching, Patrick Neven, Guy Jérusalem, J. Thaddeus Beck, Arlene Chan, Michelino De Laurentiis, Giulia Bianchi, M. Martín Jiménez, Stephen Chia, Anil Gaur, M. Sondhi, Karen Rodriguez-Lorenc, Brad Lanoue, David Chandiwana, A. Nusch

Bibliographic record

VenueAnnals of Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsBC Cancer Agency
FundersChugai PharmaceuticalGenentechServierEisaiDaiichi-SankyoDaiichi Sankyo EuropeUniversité de LiègeCurtin University of TechnologyIncyteGilead SciencesFibroGenMerck KGaAGenomic HealthAriad PharmaceuticalsAmgenPfizerNovartis Pharmaceuticals CorporationPharmaMarCelgeneBC Cancer AgencyCentro de Investigación Biomédica en Red de CáncerAstraZenecaEli Lilly and Company
KeywordsMedicineInternal medicineQuality of life (healthcare)Progression-free survivalFulvestrantPlaceboBreast cancerOncologyCancerUrologyGastroenterologyOverall survivalEstrogen receptorPathology

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.055
GPT teacher head0.358
Teacher spread0.303 · 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 designObservational
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

Citations1
Published2020
Admission routes2
Has abstractno

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