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The International Human Epigenome Consortium: A Blueprint for Scientific Collaboration and Discovery
H.G. Stunnenberg, Sergio Abrignani, David J. Adams, Melanie de Almeida, Lucia Altucci, Viren Amin, Ido Amit, Stylianos E. Antonarakis, Samuel Aparício, Takahiro Arima, Laura Arrigoni, Rob J.W. Arts, Vahid Asnafi, Manel Esteller, Jae‐Bum Bae, Kevin Baßler, Stephan Beck, Benjamin E. Berkman, B Bernstein, Mikhail Bilenky, Adrian Bird, Christoph Bock, Bernhard O. Boehm, Guillaume Bourque, Charles E. Breeze, Benedikt Brors, David Bujold, Oliver S. Burren, Marion J.G. Bussemakers, Adam S. Butterworth, Elı́as Campo, Enrique Carrillo de Santa Pau, Lisa H. Chadwick, Kui Ming Chan, Wei Chen, Tom H. Cheung, Luca Chiapperino, Ho‐Ryun Chung, Laura Clarke, Joseph M. Connors, Philippe Cronet, John Danesh, Manolis Dermitzakis, Gerard Drewes, Pawel Durek, Stephanie O. M. Dyke, Tomasz Dyląg, Connie J. Eaves, Peter Ebert, Roland Eils, Catherine Ennis, Tariq Enver, Elise A. Feingold, Bärbel Felder, Anne C. Ferguson‐Smith, Jude Fitzgibbon, Paul Flicek, Roger Foo, Peter Fraser, Mattia Frontini, Eileen E. M. Furlong, Sitanshu Gakkhar, Nina Gasparoni, Gilles Gasparoni, Daniel H. Geschwind, Petar Glažar, Thomas Graf, Frank Grosveld, Xin‐Yuan Guan, Roderic Guigó, Marta Gut, Alf Hamann, Bok-Ghee Han, R. Alan Harris, Simon Heath, Kristian Helin, Jan G. Hengstler, Alireza Heravi‐Moussavi, Karl Herrup, Steven Hill, Jason A. Hilton, Benjamin C. Hitz, Bernhard Horsthemke, Ming Hu, Jooyeon Hwang, Nancy Y. Ip, Takashi Ito, Biola M. Javierre, Sasa Jenko, Thomas Jenuwein, Yann Joly, Steven J.M. Jones, Yae Kanai, Hee Gyung Kang, Aly Karsan, Alexandra K. Kiemer, Song Cheol Kim, Bong-Jo Kim, Hiroshi Kimurâ, Sarah Kinkley, Filippos Klironomos, In-Uk Koh, Myrto Kostadima, Christopher Kressler, Roman Kreuzhuber, Anshul Kundaje, Ralf Küppers, Carolyn A. Larabell, Paul Lasko, Mark Lathrop, Daniel H. S. Lee, Suman Lee, Hans Lehrach, Elsa Leitão, Thomas Lengauer, Åke Lernmark, Richard David Leslie, Gkk Leung, Danny Leung, Markus Loeffler, Yussanne Ma, Antonello Mai, Thomas Manke, Éric Marcotte, Marco A. Marra, Joost H.A. Martens, José I. Martín‐Subero, Karen J. Maschke, Christoph A. Merten, Aleksandar Milosavljević, Saverio Minucci, Totai Mitsuyama, Richard A. Moore, Fabian Müller, Andrew J. Mungall, M. G. Netea, Karl Nordström, Iréne Norstedt, Hiroaki Okae, Vitor Onuchic, B. F. Francis Ouellette, Willem H. Ouwehand, Massimiliano Pagani, Véra Pancaldi, Thomas Pap, Tomi Pastinen, Ronak Patel, Dirk S. Paul, Michael J. Pazin, Pier Giuseppe Pelicci, Anthony G. Phillips, Julia K. Polansky, Bo Porse, J. Andrew Pospisilik, Shyam Prabhakar, Dena C. Procaccini, Andreas Radbruch, Nikolaus Rajewsky, Vardham Rakyan, Wolf Reik, Bing Ren, David Richardson, Andreas S. Richter, Daniel Rico, David J. Roberts, Philip Rosenstiel, Mark A. Rothstein, Abdulrahman Salhab, Hiroyuki Sasaki, John S. Satterlee, Sascha Sauer, C. Schacht, Florian Schmidt, Gerd Schmitz, Stefan Schreiber, Christopher Schröder, Dirk Schübeler, Joachim L. Schultze, Ronald P. Schulyer, Marcel H. Schulz, Martin Seifert, Katsuhiko Shirahige, Reiner Siebert, Thomas Sierocinski, Laura A. Siminoff, Anupam Sinha, Nicole Soranzo, Salvatore Spicuglia, Mikhail Spivakov, Christian Steidl, J. Seth Strattan, Michael Stratton, Peter Südbeck, Hao Sun, Narumi Suzuki, Yutaka Suzuki, Amos Tanay, David Torrents, Frederick L. Tyson, Thomas Ulas, Sebastian Ullrich, Toshikazu Ushijima, Alfonso Valencia, Edo Vellenga, Martin Vingron, Chris Wallace, Stefan Wallner, Jörn Walter, Huating Wang, Stephanie Weber, Andreas Weller, Andrew P. Weng, Steven P. Wilder, Sam M. Wiseman, Angela Ruohao Wu, Zhenguo Wu, Jieyi Xiong, Yasuhiro Yamashita, Xinyi Yang, Desmond Y. H. Yap, Kevin Y. Yip, Stephen Yip, Jaeil Yoo, Daniel R. Zerbino, Gideon Zipprich, Martin Hirst
Bibliographic record
VenueCell · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaBC Cancer Agency
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilNational Institute for Health and Care ResearchBritish Heart FoundationCancer Research UK
KeywordsBiologyEpigenomeBlueprintScientific discoveryComputational biologyData scienceGeneticsDNA methylationGeneComputer scienceCognitive scienceEngineering
Abstract
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 imitationNot 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)0.103
metaresearch head score (Gemma)0.067
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: Empirical · Consensus signal: none
Teacher disagreement score0.103
Threshold uncertainty score0.546
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.103 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.005 | 0.029 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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 head0.013
GPT teacher head0.264
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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
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
Citations563
Published2016
Admission routes1
Has abstractno