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Record W2222860631 · doi:10.1016/j.jtho.2015.09.006

Patients with Advanced Non–Small Cell Lung Cancer: Are Research Biopsies a Barrier to Participation in Clinical Trials?

2016· article· en· W2222860631 on OpenAlexaff
Charles Henry Lim, Frances A. Shepherd, Nazanin Nouriany, M. Sawczak, Tuhina Paul, Nicole Perera-Low, Andrea Foster, Dianne Zawisza, Ronald Feld, Geoffrey Liu, Natasha B. Leighl

Bibliographic record

VenueJournal of Thoracic Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineClinical trialLung cancerCancerInternal medicineBiopsyInformed consentOncologyPathologyAlternative 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 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)0.208
metaresearch head score (Gemma)0.487
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.208
Threshold uncertainty score0.976

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2080.487
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0030.005
Scholarly communication0.0080.007
Open science0.0030.006
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0140.003

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 head0.107
GPT teacher head0.594
Teacher spread0.487 · 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.

Study designObservational
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

Citations64
Published2016
Admission routes1
Has abstractno

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