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Record W3015289091 · doi:10.1038/s43018-020-0050-6

Pan-cancer analysis of advanced patient tumors reveals interactions between therapy and genomic landscapes

2020· article· en· W3015289091 on OpenAlexafffund
Erin Pleasance, Emma Titmuss, Laura Williamson, Harwood Kwan, Luka Culibrk, Eric Y. Stutheit-Zhao, Katherine Dixon, Kevin Yijun Fan, Reanne Bowlby, Martin Jones, Yaoqing Shen, Jasleen Grewal, Jahanshah Ashkani, Kathleen Wee, Cameron J. Grisdale, My Linh Thibodeau, Zoltán Bozóky, Hillary Pearson, Elisa Majounie, Tariq Vira, Reva Shenwai, Karen Mungall, Eric Chuah, Anna Davies, M.R. Warren, Caralyn Reisle, Melika Bonakdar, J. Paul Taylor, Veronika Csizmók, Simon K. Chan, Zusheng Zong, Steve Bilobram, Amir Muhammadzadeh, D.N. D’Souza, Richard Corbett, Daniel MacMillan, Marcus Carreira, Caleb Choo, Dustin W. Bleile, Sara Sadeghi, Wei Zhang, Tina Wong, Dean Cheng, Scott D. Brown, Robert A. Holt, Richard A. Moore, Andrew J. Mungall, Yongjun Zhao, Jessica Nelson, Alexandra Fok, Yussanne Ma, Michael K.C. Lee, Jean‐Michel Lavoie, Shehara Mendis, Joanna M. Karasinska, Balvir Deol, Ana Fisic, David F. Schaeffer, Stephen Yip, Kasmintan A. Schrader, Dean A. Regier, Deirdre Weymann, Stephen Chia, Karen A. Gelmon, Anna V. Tinker, Sophie Sun, Howard J. Lim, Daniel J. Renouf, Janessa Laskin, Steven J.M. Jones, Marco A. Marra

Bibliographic record

VenueNature Cancer · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsCanadian Centre for Applied Research in Cancer ControlVancouver General HospitalSimon Fraser UniversityBC Cancer AgencyPancreas Centre (Canada)University of British ColumbiaCanada's Michael Smith Genome Sciences Centre
FundersCanadian Institutes of Health ResearchGenome British ColumbiaCanada Foundation for InnovationGenome Canada
KeywordsTranscriptomeGenomeContext (archaeology)BiologyCancerGenome instabilityGenomicsComputational biologyDNA repairGeneGeneticsDNA damageDNAGene expression

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.284
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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations173
Published2020
Admission routes2
Has abstractno

Explore more

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