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Inherited myeloproliferative neoplasm risk affects haematopoietic stem cells
Erik L. Bao, Satish K. Nandakumar, Xiaotian Liao, Alexander G. Bick, Marcin Tabaka, Olga I. Gan, Aki S. Havulinna, Tuomo Kiiskinen, Caleb A. Lareau, Aitzkoa Lopez de Lapuente Portilla, Bo Li, Connor A. Emdin, Veryan Codd, Christopher P. Nelson, Christopher J. Walker, Claire Churchhouse, Albert de la Chapelle, Daryl E. Klein, Björn Nilsson, Peter W.F. Wilson, Kelly Cho, Saiju Pyarajan, J. Michael Gaziano, Nilesh J. Samani, Aarno Palotie, Mark J. Daly, Howard J. Jacob, Sally John, Robert M. Plenge, Mark I. McCarthy, Meg Ehm, Caroline S. Fox, Anders Mälarstig, Kathy Klinger, Kathy Call, Tomi P. Mäkelä, Jaakko Kaprio, Petri Virolainen, Kari Pulkki, Terhi Kilpi, Jukka Partanen, Anne Pitkäranta, Riitta Kaarteenaho, Seppo Vainio, Kimmo Savinainen, Veli‐Matti Kosma, Urho M. Kujala, Jeff Waring, Bridget Riley‐Gillis, Athena Matakidou, Jimmy Z. Liu, Shameek Biswas, Dawn Waterworth, Dorothée Diogo, Catherine Marshall, Xinli Hu, Matthias Gossel, Johanna Schleutker, Reetta Hinttala, Reijo Laaksonen, Arto Mannermaa, Hilkka Soininen, Valtteri Julkunen, Anne M. Remes, Reetta Kälviäinen, Mikko Hiltunen, Jukka Peltola, Pentti J. Tienari, Juha O. Rinne, Adam Ziemann, Sahar Esmaeeli, Nizar Smaoui, Susan Eaton, Sanni Lahdenperä, Janet van Adelsberg, Geoff Kerchner, Edmond Teng, John D. Eicher, Padhraig Gormley, Kari Linden, Christopher D. Whelan, Fanli Xu, David Pulford, Martti Färkkilâ, Sampsa Pikkarainen, Airi Jussila, Timo Blomster, Mikko Kiviniemi, Markku Voutilainen, Bob Georgantas, Graham Heap, Jeffrey F. Waring, Fedik Rahimov, Keith Usiskin, Joseph Maranville, Tim Lu, Natalie Bowers, Danny Oh, Kirsi Kalpala, Melissa Miller, Linda McCarthy, Kari K. Eklund, Antti Palomäki, Pia Isomäki, Laura Pirilä, Oili Kaipiainen‐Seppänen, Johanna Huhtakangas, Apinya Lertratanakul, Anne Lehtonen, David A. Close, Marla Hochfeld, Nan Bing, Jorge Esparza Gordillo, Nina Mars, Margit Pelkonen, Hannu Kankaanranta, Terttu Harju, Steven M. Greenberg, Hubert Chen, Jo Betts, Soumitra Ghosh, Veikko Salomaa, Teemu Niiranen, Markus Juonala, Kaj Metsärinne, Mika Kähönen, Juhani Junttila, Markku Laakso, Jussi Pihlajamäki, Juha Sinisalo, Marja‐Riitta Taskinen, Jari A. Laukkanen, Ben Challis, Andrew S. Peterson, Julie Hunkapiller, John A. Michon, Audrey Y. Chu, Jaakko Parkkinen, Anthony J. Muslin, Heikki Joensuu, Tuomo J Meretoja, Lauri A. Aaltonen, Annika Auranen, Peeter Karihtala, Saila Kauppila, Päivi Auvinen, Klaus Elenius, Relja Popovic, Jennifer L. Schutzman, Andrey Loboda, Aparna Chhibber, Heli Lehtonen, Stefan McDonough, Marika Crohns, Diptee Kulkarni, Kai Kaarniranta, Joni A. Turunen, Terhi Ollila, Sanna Seitsonen, Hannu Uusitalo, Vesa Aaltonen, Hannele Uusitalo‐Järvinen, Marja Luodonpää, Nina Hautala, Heiko Runz, Erich C. Strauss, Hao Chen, Anna Podgornaia, Joshua Hoffman, Kaisa Tasanen, Laura Huilaja, Katariina Hannula‐Jouppi, Teea Salmi, Sirkku Peltonen, Leena Koulu, Ilkka T. Harvima, Ying Wu, David F. Choy, J. Wade Davis, Danjuma Quarless, Slavé Petrovski, Chia‐Yen Chen, Paola G. Bronson, Robert Yang, Diana Chang, Tushar Bhangale, Emily Holzinger, Xulong Wang, Xing Chen, Åsa K. Hedman, Kirsi Auro, Clarence Wang, Ethan Xu, Franck Augé, Clément Chatelain, Juha Karjalainen, Anu Jalanko, Kimmo Palin, Priit Palta, Pietro Della Briotta Parolo, Wei Zhou, Manuel A. Rivas, Arto Lehistö, Andrea Ganna, Vincent Llorens, Antti Karlsson, Kati Hyvärinen, Jarmo Ritari, Tiina Wahlfors, Miika Koskinen, Olli Carpén, Katri Pylkäs, Marita Kalaoja, Minna K. Karjalainen, Tuomo Mantere, Eeva Kangasniemi, Sami Heikkinen, Eija K. Laakkonen, Juha Kononen, Lila Kallio, Sirpa Soini, Kimmo Pitkänen, Teijo Kuopio, Risto Kajanne, Ulrike Lyhs, Pietro della Briotta Parola, Sina Rüeger, Masahiro Kanai, Hannele Laivuori, Susanna Lemmelä, Mari Kaunisto, Elina Kilpeläinen, Timo P. Sipilä, Georg Brein, Oluwaseun Alexander Dada, Awaisa Ghazal, Anastasia Shcherban, Tuomas Sipilä, Kati Donner, Anu Loukola, Päivi Laiho, Tuuli Sistonen, Essi Kaiharju, Markku Laukkanen, Elina Järvensivu, Sini Lähteenmäki, Lotta Männikkö, Regis Wong, Hannele Mattsson, Tero Hiekkalinna, Manuel González Jiménez, Kalle Pärn, Javier Núñez-Fontarnau, Harri Siirtola, Javier Gracia‐Tabuenca, Michelle Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson, Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Karen E. Huber, Aaron Kleinman, Nadia K. Litterman, Jennifer C. McCreight, Matthew H. McIntyre, Joanna L. Mountain, Elizabeth S. Noblin, Carrie A. M. Northover, Steven J. Pitts, J. Fah Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao Tian, Joyce Y. Tung, Vladimir Vacic, Catherine H. Wilson, Aviv Regev, Benjamin M. Neale, John E. Dick, Pradeep Natarajan, Christopher J. O’Donnell, Michael Milyavsky, Sekar Kathiresan, Vijay G. Sankaran
Bibliographic record
VenueNature · 2020
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institutes of HealthU.S. Department of Veterans AffairsHoward Hughes Medical Institute
KeywordsHaematopoiesisBiologyStem cellMyeloproliferative neoplasmGeneticsMyeloidSomatic cellCancer researchImmunologyGeneBone marrowMyelofibrosis
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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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 designBench or experimental
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
Citations148
Published2020
Admission routes1
Has abstractno