MétaCan
Menu
Back to cohort
Record W2595991414 · doi:10.1016/j.ccell.2017.02.010

Integrated Molecular Characterization of Uterine Carcinosarcoma

2017· article· en· W2595991414 on OpenAlexaff
Andrew D. Cherniack, Hui Shen, Vonn Walter, Chip Stewart, Bradley A. Murray, Reanne Bowlby, Xin Hu, Shiyun Ling, Robert A. Soslow, Russell R. Broaddus, Rosemary E. Zuna, Gordon Robertson, Peter W. Laird, Raju Kucherlapati, Gordon B. Mills, Adrian Ally, J. Todd Auman, Miruna Balasundaram, Saianand Balu, Stephen B. Baylin, Rameen Beroukhim, Tom Bodenheimer, Faina Bogomolniy, Lori Boice, Jay Bowen, Denise Brooks, Rebecca Carlsen, Juok Cho, Eric Chuah, Sudha Chudamani, Kristian Cibulskis, Melissa Cline, Fanny Dao, Mutch David, John A. Demchok, Noreen Dhalla, Sean C. Dowdy, Ina Felau, Martin L. Ferguson, Scott Frazer, Jessica Frick, Stacey Gabriel, Julie M. Gastier‐Foster, Nils Gehlenborg, Mark Gerken, Gad Getz, Manaswi Gupta, David Haussler, D. Neil Hayes, David I. Heiman, Julian M. Hess, Katherine A. Hoadley, Robert Hoffmann, Robert A. Holt, Alan P. Hoyle, Mei Huang, Carolyn M. Hutter, Steven J.M. Jones, Corbin D. Jones, Rupa S. Kanchi, Cyriac Kandoth, Sarah E. Kerr, Jaegil Kim, Phillip H. Lai, Eric S. Lander, Michael S. Lawrence, Darlene Lee, Kristen Leraas, Ignaty Leshchiner, Tara M. Lichtenberg, Pei Lin, Jia Liu, Wenbin Liu, Yuexin Liu, Laxmi Lolla, Yiling Lu, Yussanne Ma, Dennis T. Maglinte, Marco A. Marra, Michael Mayo, Shaowu Meng, Matthew Meyerson, Piotr A. Mieczkowski, Richard A. Moore, Lisle E. Mose, Andrew J. Mungall, Karen Mungall, Rashi Naresh, Michael S. Noble, Narciso Olvera, Joel S. Parker, Charles M. Perou, Amy H. Perou, Todd Pihl, Amie Radenbaugh, Nilsa C. Ramirez, W. Kimryn Rathmell, Jeffrey Roach, A. Gordon Robertson, Sara Sadeghi, Gordon Saksena, Helga B. Salvesen, Jacqueline E. Schein, Steven E. Schumacher, Margi Sheth, Yan Shi, Juliann Shih, Janae V. Simons, Payal Sipahimalani, Tara Skelly, Heidi J. Sofia, Matthew G. Soloway, Carrie Sougnez, Charlie Sun, Angela Tam, Donghui Tan, Roy Tarnuzzer, Nina Thiessen, Leigh B. Thorne, Kane Tse, Jill Tseng, David Van Den Berg, Umadevi Veluvolu, Roel G.W. Verhaak, Doug Voet, Amanda von Bismarck, Yunhu Wan, Chen Wang, John N. Weinstein, Daniel J. Weisenberger, Matthew D. Wilkerson, Boris Winterhoff, Lisa Wise, Tina Wong, Ye Wu, Liming Yang, Jean C. Zenklusen, Jiashan Zhang, Hailei Zhang, Wei Zhang, Jingchun Zhu, Erik Zmuda

Bibliographic record

VenueCancer Cell · 2017
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsCanada's Michael Smith Genome Sciences CentreBC Cancer Agency
FundersNational Cancer InstituteNational Human Genome Research InstituteNational Institutes of Health
KeywordsPTENBiologySomatic cellCarcinosarcomaKRASEpigeneticsCancer researchTranscriptomeEpigenomicsGeneGNAQSerous fluidDNA methylationCarcinomaGeneticsMutationPI3K/AKT/mTOR pathwayGene 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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.300
Teacher spread0.278 · 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

Citations444
Published2017
Admission routes1
Has abstractno

Explore more

Same venueCancer CellSame topicSarcoma Diagnosis and TreatmentFrench-language works237,207