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Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion
Isabelle Cleynen, Worrawat Engchuan, Matthew S. Hestand, Tracy Heung, Aaron M. Holleman, H. Richard Johnston, Thomas Monfeuga, Donna M. McDonald‐McGinn, Raquel E. Gur, Bernice E. Morrow, Ann Swillen, Jacob Vorstman, Carrie E. Bearden, Eva W. C. Chow, Marianne B. M. van den Bree, B S Emanuel, Joris Vermeesch, Stephen T. Warren, Michael J. Owen, Pankaj Chopra, David J. Cutler, Richard Duncan, Alex Kotlar, Jennifer G. Mulle, Anna J. Voss, Michael E. Zwick, Alexander Diacou, Aaron Golden, Tingwei Guo, Jhih-Rong Lin, Tao Wang, Zhengdong Zhang, Yingjie Zhao, Christian R. Marshall, Daniele Merico, Andrea Jin, Brenna Lilley, Harold I. Salmons, Oanh Tran, Peter Holmans, Antonio F. Pardiñas, James Walters, Wolfram Demaerel, Erik Boot, Nancy J. Butcher, Gregory Costain, Chelsea Lowther, Rens Evers, Thérèse van Amelsvoort, Esther van Duin, Claudia Vingerhoets, Jeroen Breckpot, Koenraad Devriendt, Elfi Vergaelen, Annick Vogels, T. Blaine Crowley, Daniel E. McGinn, Edward Moss, Robert Sharkus, Marta Unolt, Elaine H. Zackai, Monica E. Calkins, Robert S. Gallagher, Ruben C. Gur, Sunny X. Tang, Rosemarie Fritsch, Claudia Ornstein, Gabriela M. Repetto, Elemi Breetvelt, Sasja N. Duijff, Ania Fiksinski, Hayley Moss, Maria Niarchou, Kieran C. Murphy, Sarah E. Prasad, Eileen Daly, Maria Gudbrandsen, Clodagh M. Murphy, Declan Murphy, Antonio Buzzanca, Fabio Di Fabio, Maria Cristina Digilio, Maria Pontillo, Bruno Marino, Stefano Vicari, Karlene Coleman, Joseph F. Cubells, Opal Ousley, Miri Carmel, Doron Gothelf, Ehud Mekori‐Domachevsky, Elena Michaelovsky, Ronnie Weinberger, Abraham Weizman, Leila Kushan, Maria Jalbrzikowski, Marco Armando, Stéphan Eliez, Corrado Sandini, Maude Schneider, Frédérique Béna, Kevin M. Antshel, Wanda Fremont, Wendy R. Kates, Raoul Belzeaux, Tiffany Busa, Nicole Philip, Linda Campbell, Kathryn McCabe, Stephen R. Hooper, Kelly Schoch, Vandana Shashi, Tony J. Simon, Flora Tassone, Celso Arango, David Fraguas, Sixto García‐Miñáur, Jaume Morey-Canyelles, Jordi Rosell, Damián Heine‐Suñer, Jasna Raventos-Simic, Michael P. Epstein, Nigel Williams, Anne S. Bassett
Bibliographic record
VenueMolecular Psychiatry · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsOntario GenomicsUniversity of TorontoSickKids FoundationToronto General HospitalUniversity Health NetworkCentre for Addiction and Mental HealthHospital for Sick Children
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesNational Institute of Mental HealthMedical Research CouncilNational Science FoundationCanadian Institutes of Health ResearchJohns Hopkins UniversityNational Center for Mental HealthFonds Wetenschappelijk OnderzoekWellcome TrustNational Alliance for Research on Schizophrenia and DepressionSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Institutes of HealthMinisterio de Economía y Competitividad
KeywordsSchizophrenia (object-oriented programming)Polygenic risk scorePopulationGenome-wide association studyDiGeorge syndromeGeneticsPsychosisGenetic associationDeletion syndromePsychiatryBiologyPsychologyMedicineGeneSingle-nucleotide polymorphismGenotypePhenotype
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)0.003
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 score0.005
Threshold uncertainty score0.016
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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 head0.007
GPT teacher head0.255
Teacher spread0.249 · 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
Citations135
Published2020
Admission routes2
Has abstractno