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Record W2096920403 · doi:10.1038/ng.2293

Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk

2012· review· en· W2096920403 on OpenAlexaff
Malcolm G. Dunlop, Sara E. Dobbins, Susan M. Farrington, Angela M. Jones, Claire Palles, Nicola Whiffin, Albert Tenesa, Sarah L. Spain, Peter Broderick, Li Yin Ooi, Enric Domingo, Claire Smillie, Marc Henrion, Matthew Frampton, Lynn Martin, Graeme R. Grimes, Maggie Gorman, Colin A. Semple, P Yusanne, Ella Barclay, James Prendergast, Jean‐Baptiste Cazier, Bianca Olver, Steven Penegar, Steven Lubbe, Ian Chander, Luis G. Carvajal‐Carmona, Stéphane Ballereau, Amy Lloyd, Jayaram Vijayakrishnan, Lina Zgaga, Igor Rudan, Evropi Τheodoratou, John M. Starr, Ian J. Deary, Iva Kirac, Dujo Kovačević, Lauri A. Aaltonen, Laura Renkonen‐Sinisalo, Jukka‐Pekka Mecklin, Koichi Matsuda, Yusuke Nakamura, Yukinori Okada, Steven Gallinger, David Duggan, David V. Conti, Polly A. Newcomb, John L. Hopper, Mark A. Jenkins, Fredrick R. Schumacher, Graham Casey, Douglas Easton, Mitul Shah, Paul D.P. Pharoah, Annika Lindblom, Tao Liu, Christopher G. Smith, Hannah D. West, Jeremy P. Cheadle, Rachel Midgley, David Kerr, Harry Campbell, Ian Tomlinson, Richard S. Houlston

Bibliographic record

VenueNature Genetics · 2012
Typereview
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersNational Cancer InstituteBiotechnology and Biological Sciences Research CouncilCancer Research UKWellcome Trust
KeywordsColorectal cancerBiologyGeneticsGenome-wide association studyCase-control studyGenetic associationCancerInternal medicineSingle-nucleotide polymorphismGeneGenotypeMedicine

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.349
Teacher spread0.323 · 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 designSystematic review
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

Citations232
Published2012
Admission routes1
Has abstractno

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