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Record W2559804019 · doi:10.1016/s0140-6736(16)32455-2

Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial

2016· article· en· W2559804019 on OpenAlexaff
Arjun Vasant Balar, Matthew D. Galsky, Jonathan E. Rosenberg, Thomas Powles, Daniel P. Petrylak, Joaquim Bellmunt, Yohann Loriot, Andrea Necchi, Jean Hoffman‐Censits, José Luis Perez‐Gracia, Nancy A. Dawson, Michiel S. van der Heijden, Robert Dreicer, Sandy Srinivas, Margitta Retz, Richard W. Joseph, Alexandra Drakaki, Ulka N. Vaishampayan, Srikala S. Sridhar, David I. Quinn, Ignacio Durán, David R. Shaffer, Bernhard J. Eigl, Petros Grivas, Evan Y. Yu, Shi Li, Edward E. Kadel, Zachary Boyd, Richard Bourgon, Priti S. Hegde, Sanjeev Mariathasan, AnnChristine Thåström, Oyewale O. Abidoye, Gregg Fine, Dean F. Bajorin

Bibliographic record

VenueThe Lancet · 2016
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsBC Cancer AgencyPrincess Margaret Cancer Centre
FundersNational Cancer InstituteEMD SeronoIpsenAstellas PharmaF. Hoffmann-La RocheEisaiSanofiAmgenPfizerGenentechCelgeneAstraZenecaEli Lilly and Company
KeywordsAtezolizumabMedicineMetastatic Urothelial CarcinomaClinical endpointOncologyInternal medicineCisplatinChemotherapyProgression-free survivalPhases of clinical researchResponse Evaluation Criteria in Solid TumorsCancerBladder cancerUrologyClinical trialUrothelial carcinomaImmunotherapyPembrolizumab

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)0.002
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.305
Teacher spread0.270 · 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

Citations2,211
Published2016
Admission routes1
Has abstractno

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