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Identification of 371 genetic variants for age at first sex and birth linked to externalising behaviour
Melinda Mills, Felix C. Tropf, David M. Brazel, Natalie R. van Zuydam, Ahmad Vaez, Mawussé Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Philip Awadalla, Alexis Battle, Frank Beutner, Dorret I. Boomsma, Mark Christiansen, Annique Claringbould, Patrick Deelen, Tõnu Esko, Marie-Julie Favé, Timothy M. Frayling, Sina A. Gharib, Greg Gibson, Gibran Hemani, Mika Kähönen, Anette Kalnapenkis, Silva Kasela, Johannes Kettunen, Yungil Kim, Holger Kirsten, Péter Kovács, Knut Krohn, Jaanika Kronberg, Viktorija Kukushkina, Zoltán Kutalik, Bernett Lee, Terho Lehtimäki, Markus Loeffler, Urko M. Marigorta, Hailang Mei, Lili Milani, Grant W. Montgomery, Martina Müller‐Nurasyid, Matthias Nauck, Michel G. Nivard, Brenda W.J.H. Penninx, Markus Perola, Natalia Pervjakova, Brandon L. Pierce, Joseph E. Powell, Holger Prokisch, Bruce M. Psaty, Olli T. Raitakari, Samuli Ripatti, Olaf Rötzschke, Sina Rüeger, Ashis Saha, Markus Scholz, Katharina Schramm, Ilkka Seppälä, P. Eline Slagboom, Coen D.A. Stehouwer, Michael Stümvoll, Patrick Sullivan, Peter A.C. ’t Hoen, Alexander Teumer, Joachim Thiery, Tong Lin, Anke Tönjes, Jenny van Dongen, Jan H. Veldink, Joost Verlouw, Peter M. Visscher, Uwe Völker, Urmo Võsa, Harm-Jan Westra, Cisca Wijmenga, Hanieh Yaghootkar, Jian Yang, Biao Zeng, Futao Zhang, Bastiaan T. Heijmans, Aaron Isaacs, Lude Franke, René Pool, Marleen M. J. van Greevenbroek, Carla Kallen, Casper G. Schalkwijk, Sasha Zhernakova, Ettje F. Tigchelaar, Marian Beekman, Joris Deelen, Leonard H. van den Berg, Cornelia M. van Duijn, Bert A. Hofman, André G. Uitterlinden, Joyce B. J. van Meurs, P. Mila Jhamai, Michaël Verbiest, H. Eka D. Suchiman, Marijn Verkerk, Ruud van der Breggen, Jeroen van Rooij, Nico Lakenberg, Hailiang Mei, Maarten van Iterson, Jan Bot, Dasha V. Zhernakova, Peter van ‘t Hof, Irene Nooren, Matthijs Moed, Martijn Vermaat, René Luijk, Freerk van Dijk, Szymon M. Kiełbasa, Morris A. Swertz, Erik W. van Zwet, Evelina T. Akimova, Sven Bergmann, Marco Brumat, Julie E. Buring, David Cesarini, Daniel I. Chasman, Jorge E. Chavarro, Massimiliano Cocca, Maria Pina Concas, Gail Davies, Ian J. Deary, Oscar H. Franco, Audrey J. Gaskins, Eco J. C. de Geus, Christian Gieger, Giorgia Girotto, Hans J. Grabe, Erica P. Gunderson, Kathleen Mullan Harris, Fernando Pires Hartwig, Chunyan He, W. David Hill, Georg Homuth, Bernando Lessa Horta, Hongyang Huang, Elina Hyppönen, M. Arfan Ikram, Rick Jansen, Magnus Johannesson, Zoha Kamali, Maryam Kavousi, Peter Kraft, Brigitte Kühnel, Claudia Langenberg, Penelope A. Lind, Jian’an Luan, Reedik Mägi, Patrik K. E. Magnusson, Anubha Mahajan, Nicholas G. Martin, Hamdi Mbarek, Mark I. McCarthy, George McMahon, Matthew B. McQueen, Sarah E. Medland, Thomas Meitinger, Andres Metspalu, Evelin Mihailov, Stacey A. Missmer, Stine Møllegaard, Dennis O. Mook‐Kanamori, Anna Morgan, Peter J. van der Most, Renée de Mutsert, Ilja M. Nolte, Raymond Noordam, Annette Peters, Chris Power, Paul Redmond, Janet W. Rich‐Edwards, Paul M. Ridker, Cornelius A. Rietveld, Susan M. Ring, Lynda M. Rose, Rico Rueedi, Kāri Stefánsson, Doris Stöckl, Konstantin Strauch, Guðmar Þorleifsson, Unnur Þorsteinsdóttir, Roy Thurik, Nicholas J. Timpson, Constance Turman, Mélanie Waldenberger, Nicholas J. Wareham, Gonneke Willemsen, Jing Zhao, Tune H. Pers, Harold Snieder, John R. B. Perry, Ken K. Ong, Marcel den Hoed, Nicola Barban, Felix R. Day
Bibliographic record
VenueNature Human Behaviour · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsOntario Institute for Cancer Research
FundersGenentechHjärt-LungfondenServierLundbeckfondenUniversity of OxfordLeverhulme TrustNovo NordiskNational Institute for Health and Care ResearchWellcome TrustAgence Nationale de la RechercheMedical Research CouncilInternational Seafood Sustainability FoundationEconomic and Social Research CouncilSanofiEli Lilly and CompanyUK Research and InnovationVetenskapsrådetPfizer
KeywordsIdentification (biology)Sex linkageGeneticsBiologyComputational biologyEvolutionary biologyGeneChromosome
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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 head0.015
GPT teacher head0.301
Teacher spread0.286 · 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 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
Citations163
Published2021
Admission routes1
Has abstractno