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Record W2948640002 · doi:10.1038/s41593-019-0402-7

Author Correction: GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability

2019· erratum· en· W2948640002 on OpenAlexaff
Joëlle A. Pasman, Karin J. H. Verweij, Zachary Gerring, Sven Stringer, Sandra Sanchez‐Roige, Jorien L. Treur, Abdel Abdellaoui, Michel G. Nivard, Bart M. L. Baselmans, Jue‐Sheng Ong, Hill F. Ip, Matthijs D. van der Zee, Meike Bartels, Felix R. Day, Pierre Fontanillas, Sarah L. Elson, Harriet de Wit, Lea K. Davis, James MacKillop, Jaime Derringer, Susan Branje, Catharina A. Hartman, Andrew C. Heath, P.A.C. van Lier, Pamela A. F. Madden, Reedik Mägi, Wim Meeus, Grant W. Montgomery, Albertine J. Oldehinkel, Zdenka Pausová, Josep Antoni Ramos‐Quiroga, Tomáš Paus, Marta Ribasés, Jaakko Kaprio, Marco P. Boks, Jordana T. Bell, Tim D. Spector, Joel Gelernter, Dorret I. Boomsma, Nicholas G. Martin, Stuart MacGregor, John R. B. Perry, Abraham A. Palmer, Daniëlle Posthuma, Marcus R. Munafò, Nathan A. Gillespie, Eske M. Derks, Jacqueline M. Vink

Bibliographic record

VenueNature Neuroscience · 2019
Typeerratum
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoMcMaster UniversityBaycrest HospitalSt. Joseph’s Healthcare Hamilton
FundersMedical Research Council
KeywordsSchizophrenia (object-oriented programming)Genome-wide association studyCannabisPsychologyLiabilityPsychiatryPsychiatric geneticsClinical psychologyNeuroscienceSingle-nucleotide polymorphismGeneticsBiologyGeneGenotype

Abstract

fetched live from OpenAlex
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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.000

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 head0.281
Teacher spread0.274 · 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 teacher head, not a consensus.

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

Citations32
Published2019
Admission routes1
Has abstractno

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