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Record W4411932276 · doi:10.1038/s41586-025-09219-0

The mutagenic forces shaping the genomes of lung cancer in never smokers

2025· article· en· W4411932276 on OpenAlexaff
Marcos Díaz‐Gay, Tongwu Zhang, Phuc H. Hoang, Charles Leduc, Marina K. Baine, William D. Travis, Lynette M. Sholl, Philippe Joubert, Azhar Khandekar, Zhao Wei, Christopher D. Steele, Burçak Otlu, Shuvro P. Nandi, Raviteja Vangara, Erik N. Bergstrom, Mariya Kazachkova, Oriol Pich, Charles Swanton, Chao A. Hsiung, I-Shou Chang, Maria Pik Wong, Kin Chung Leung, Jian Sang, John McElderry, Caleb Hartman, Frank J. Colón-Matos, Mona Miraftab, Monjoy Saha, Olivia W. Lee, Kristine Jones, Pilar Gallego‐García, Yang Yang, Xiaoming Zhong, Eric S. Edell, Juan Miguel Santamaría, Matthew B. Schabath, Sai Yendamuri, Marta Mańczuk, Jolanta Lissowska, Beata Świątkowska, Anush Mukeria, Oxana Shangina, David Zaridze, Ivana Holcátová, Dana Mateș, Saša Milosavljević, Milica Kontić, Yohan Bossé, Bonnie E. Gould Rothberg, David C. Christiani, Valérie Gaborieau, Paul Brennan, Geoffrey Liu, Paul Hofman, Lixing Yang, Martin A. Nowak, Jianxin Shi, Nathaniel Rothman, David C. Wedge, Robert Homer, Soo‐Ryum Yang, Angela Cecilia Pesatori, Dario Consonni, Qing Lan, Bin Zhu, Stephen J. Chanock, Jiyeon Choi, Ludmil B. Alexandrov, Maria Teresa Landi

Bibliographic record

VenueNature · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversité LavalInstitut universitaire de cardiologie et de pneumologie de QuébecCentre Hospitalier de l’Université de Montréal
FundersNational Institute of Environmental Health SciencesNational Cancer InstituteNational Institutes of HealthWorld Health Organization
KeywordsLung cancerGenomeBiologyGeneticsComputational biologyMedicineOncologyGene

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.004
GPT teacher head0.277
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations37
Published2025
Admission routes1
Has abstractno

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