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Record W2925139051 · doi:10.1016/j.jtho.2019.03.007

Updated Efficacy and Safety Data and Impact of the EML4-ALK Fusion Variant on the Efficacy of Alectinib in Untreated ALK-Positive Advanced Non–Small Cell Lung Cancer in the Global Phase III ALEX Study

2019· article· en· W2925139051 on OpenAlexaff
D. Ross Camidge, Rafał Dziadziuszko, Solange Peters, Tony Mok, Johannes Noé, Małgorzata Nowicka, Shirish M. Gadgeel, Parneet Cheema, Nick Pavlakis, Filippo de Marinis, Byoung Chul Cho, Li Zhang, Denis Moro‐Sibilot, Ting Liu, Walter Bordogna, Bogdana Balas, Bárbara Müller, Alice T. Shaw

Bibliographic record

VenueJournal of Thoracic Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersMerck Sharp and DohmeGenentechF. Hoffmann-La RocheAmgenAriad PharmaceuticalsRocheNovartisCelgeneBristol-Myers SquibbAstraZenecaPfizerAbbVieMerck
KeywordsAlectinibMedicineLung cancerCrizotinibOncologyInternal medicineCancer research

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.008
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.449
Teacher spread0.431 · 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 designRandomized 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

Citations491
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Thoracic Oncology→Same topicLung Cancer Treatments and Mutations→French-language works237,207→