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Record W3087055096 · doi:10.1038/s41436-020-0892-4

Correction: Cancer risks by gene, age, and gender in 6350 carriers of pathogenic mismatch repair variants: findings from the Prospective Lynch Syndrome Database

2020· erratum· en· W3087055096 on OpenAlexaff
Mev Dominguez–Valentin, Julian R. Sampson, Toni T. Seppälä, Sanne W. ten Broeke, John‐Paul Plazzer, Sigve Nakken, Christoph Engel, Stefan Aretz, Mark A. Jenkins, Lone Sunde, Inge Bernstein, Gabriel Capellá, Francesc Balaguer, Huw Thomas, D. Gareth Evans, John Burn, Marc S. Greenblatt, Eivind Hovig, Wouter H. de Vos tot Nederveen Cappel, Rolf H. Sijmons, Lucio Bertario, Maria Grazia Tibiletti, Giulia Martina Cavestro, Annika Lindblom, Adriana Della Valle, Francisco López‐Köstner, Nathan Gluck, Lior H. Katz, Karl Heinimann, Carlos Vaccaro, Reinhard Büttner, Heike Görgens, Elke Holinski‐Feder, Monika Morak, Stefanie Holzapfel, Robert Hüneburg, Magnus von Knebel Doeberitz, Markus Loeffler, Nils Rahner, Hans K. Schackert, Verena Steinke‐Lange, Wolff Schmiegel, Deepak Vangala, Kirsi Pylvänäinen, Laura Renkonen‐Sinisalo, John L. Hopper, Aung Ko Win, Robert W. Haile, Noralane M. Lindor, Steven Gallinger, Loı̈c Le Marchand, Polly A. Newcomb, Jane C. Figueiredo, Stephen N. Thibodeau, Karin Wadt, Christina Therkildsen, Henrik Okkels, Zohreh Ketabi, Leticia Moreira, Ariadna Sánchez, Miquel Serra‐Burriel, Marta Pineda, Matilde Navarro, Ignacio Blanco, Kate Green, Fiona Lalloo, Emma J. Crosbie, James Hill, Oliver G. Denton, Ian M. Frayling, Einar Andreas Rødland, Hans F. A. Vasen, Miriam Mints, Florencia Neffa, Patricia Esperón, Karin Álvarez, Revital Kariv, Guy Rosner, Tamara Alejandra Piñero, María Laura González, Pablo Kalfayan, Douglas Tjandra, Ingrid Winship, Finlay Macrae, Gabriela Möslein, Jukka‐Pekka Mecklin, Maartje Nielsen, Pål Møller

Bibliographic record

VenueGenetics in Medicine · 2020
Typeerratum
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersNational Institute for Health and Care Research
KeywordsLynch syndromeMedicineBioinformaticsCancerGeneticsDNA mismatch repairDatabaseInternal medicineBiologyComputer scienceColorectal cancer

Abstract

fetched live from OpenAlex

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.003
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.117
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.061
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1170.041

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 head0.044
GPT teacher head0.320
Teacher spread0.276 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations11
Published2020
Admission routes1
Has abstractyes

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