MétaCan
Menu
Back to cohort
Record W2620097568 · doi:10.1016/j.jtho.2017.05.019

Scientific Advances in Thoracic Oncology 2016

2017· review· en· W2620097568 on OpenAlexaff
Ross A. Soo, Emily Stone, K. Michael Cummings, James R. Jett, John K. Field, Harry J.M. Groen, James L. Mulshine, Yasushi Yatabe, Lukas Bubendorf, Sanja Đačić, Ramón Rami–Porta, Frank C. Detterbeck, Eric Lim, Hisao Asamura, Jessica Donington, Heather A. Wakelee, Yi‐Long Wu, Kristin Higgins, Suresh Senan, Benjamin Solomon, Dong‐Wan Kim, Melissa L. Johnson, James Chih‐Hsin Yang, Lecia V. Sequist, Alice T. Shaw, Myung‐Ju Ahn, Daniel B. Costa, Jyoti D. Patel, Leora Horn, Scott Gettinger, Solange Peters, Murry W. Wynes, Corinne Faivre‐Finn, Charles M. Rudin, Anne S. Tsao, Ronan J. Kelly, Natasha B. Leighl, Giorgio V. Scagliotti, David R. Gandara, Fred R. Hirsch, David R. Spigel

Bibliographic record

VenueJournal of Thoracic Oncology · 2017
Typereview
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersFoundation MedicineLoxo OncologyPharmacyclicsChugai PharmaceuticalEMD SeronoGenentechMedelaAstellas PharmaDaiichi-SankyoTaiho PharmaceuticalNational Institutes of HealthRegeneron PharmaceuticalsMeiji Seika PharmaAmerican Cancer SocietyShionogiHelsinnMirati TherapeuticsClovis OncologyVarian Medical SystemsAriad PharmaceuticalsCancer Research UKArray BioPharmaNational Cancer InstituteGilead SciencesExelixisSanofiG1 TherapeuticsCelgeneAstraZenecaIgnytaEli Lilly and CompanyBristol-Myers SquibbPfizer
KeywordsMedicineLung cancerTargeted therapyImmunotherapyOncologyRadiation therapyInternal medicineRadiation oncologyMedical physicsCancerIntensive care medicine

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.097
GPT teacher head0.591
Teacher spread0.494 · 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 designOther design
Domainnot available
GenreReview

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

Citations57
Published2017
Admission routes1
Has abstractno

Explore more

Same venueJournal of Thoracic OncologySame topicLung Cancer Treatments and MutationsFrench-language works237,207