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Record W4392641667 · doi:10.1055/s-0044-1781403

Pneumologische Onkologie Tumor Treating Fields (TTFields) therapy with standard systemic therapy in metastatic non-small cell lung cancer following progression on or after platinum-based therapy: global randomized, pivotal (phase 3) LUNAR study

2024· article· en· W4392641667 on OpenAlex
Richard Greil, Ticiana Leal, Rupesh Kotecha, Rodryg Ramlau, Li Zhang, Janusz Milanowski, Manuel Cobo, J Roubec, Luboš Petruželka, Libor Havel, Sujith Kalmadi, John H. Ward, Zoran Andrić, Thierry Berghmans, David E. Gerber, Goetz Kloecker, Rajiv Panikkar, Joachim G.J.V. Aerts, Angelo Delmonte, Miklos Pless, Christian Rolfo, Matthew D. Eaton, M.S. Iqbal, Wallace Akerley, Corey J. Langer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePneumologie · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineSystemic therapyLung cancerOncologyCancerRandomized controlled trialInternal medicineBreast cancer

Abstract

fetched live from OpenAlex

Background: TTFields are electric fields that disrupt cancer cell viability. TTFields therapy is approved for glioblastoma and mesothelioma. The randomized, pivotal (phase 3) LUNAR study (NCT02973789) assessed the efficacy and safety of TTFields therapy with investigator's choice of standard systemic therapy (ST; immune checkpoint inhibitor [ICI] or docetaxel [DTX], standard of care at time of study design) for metastatic non-small cell lung cancer (mNSCLC) progressing on/after platinum-based therapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.389
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