{"id":"W4213317798","doi":"10.1002/jcv2.12063","title":"A multi‐informant and multi‐polygenic approach to understanding predictors of peer victimisation in childhood and adolescence","year":2022,"lang":"en","type":"article","venue":"JCPP Advances","topic":"Cognitive Abilities and Testing","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université du Québec à Montréal; Université de Montréal; Université Laval","funders":"Economic and Social Research Council; Fonds de Recherche du Québec - Santé; Université Laval; Université de Montréal; Social Sciences and Humanities Research Council of Canada; Fonds de Recherche du Québec-Société et Culture; Canadian Institutes of Health Research","keywords":"Victimisation; Polygenic risk score; Psychology; Developmental psychology; Clinical psychology; Medicine; Human factors and ergonomics; Poison control; Environmental health; Genetics; Single-nucleotide polymorphism; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002686779,0.00009144045,0.0001358341,0.000122154,0.0001164731,0.0000105313,0.00006179976,0.00002195382,0.00003074166],"category_scores_gemma":[0.0001202514,0.00009124172,0.00001779381,0.0001931103,0.00006516572,0.0001415449,0.0001087167,0.0001403591,6.077981e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006107174,"about_ca_system_score_gemma":0.00001414321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009000422,"about_ca_topic_score_gemma":0.00006183835,"domain_scores_codex":[0.999181,0.00005003554,0.0002063116,0.0002373506,0.0001510124,0.0001743209],"domain_scores_gemma":[0.9996367,0.0001235721,0.00008104926,0.00008996361,0.00002175208,0.00004696867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001184765,0.000443751,0.9092337,0.0001033235,0.0000300899,0.000002705196,0.0640812,0.0006986107,0.0001856814,0.001723641,0.0000201594,0.02335865],"study_design_scores_gemma":[0.00149616,0.0001982932,0.9166096,0.0000385173,0.00001258649,0.00002133884,0.0767884,0.004018106,0.00002179483,0.0003096644,0.0003285791,0.0001569215],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905672,0.0009618246,0.005356922,0.0001301622,0.0001651108,0.0004436558,0.0000334406,0.00002790905,0.002313766],"genre_scores_gemma":[0.9964397,0.00002109195,0.003232726,0.00007887778,0.00001995903,0.00007249341,0.000007136346,0.000009055429,0.0001189731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02320173,"threshold_uncertainty_score":0.372073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04602974666035942,"score_gpt":0.2981893896897045,"score_spread":0.2521596430293451,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}