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Record W3087842901 · doi:10.1016/j.annonc.2020.08.438

336P PI3K pathway biomarkers and clinical response in a phase I/Ib study of GDC-0077 in hormone receptor-positive/HER2-negative breast cancer (HR+/HER2– BC)

2020· article· en· W3087842901 on OpenAlexaff
Valentina Gambardella, Andrés Cervantes, Philippe L. Bédard, Erika Hamilton, Antoîne Italiano, Komal Jhaveri, Dejan Juric, Kevin Kalinsky, IE Krop, Mafalda Oliveira, Cristina Saura, Peter Schmid, Nicholas C. Turner, Andréa Varga, B.P. Liu, J.W. Chen, Junko Aimi, Stephanie Royer‐Joo, Jennifer L. Schutzman, Katherine E. Hutchinson

Bibliographic record

VenueAnnals of Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersEMD SeronoGenentechPharmaMarSpringworks TherapeuticsMacroGenicsSilverback TherapeuticsCilagPuma BiotechnologyRelay TherapeuticsEisaiCelltrionSyndax PharmaceuticalsDaiichi Sankyo EuropeNational Cancer InstituteServierCalithera BiosciencesUnum TherapeuticsAmgenRadius HealthClovis OncologyLes Laboratories Pierre FabreGenomic HealthIpsenArray BioPharmaMersana TherapeuticsKaryopharm TherapeuticsNuCanaPfizerIncyteTaiho PharmaceuticalF. Hoffmann-La RocheGlaxoSmithKlineJounce TherapeuticsPTC TherapeuticsCelgeneCancer Research InstituteAstraZenecaEli Lilly and CompanyBristol-Myers SquibbSanofi
KeywordsMedicinePalbociclibBreast cancerInternal medicineFulvestrantOncologyCancerEstrogen receptorMetastatic breast cancer

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.093
GPT teacher head0.452
Teacher spread0.359 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations0
Published2020
Admission routes1
Has abstractno

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