{"id":"W4214549042","doi":"10.31234/osf.io/bhpm5","title":"Neither nature nor nurture: Using extended pedigree data to understand indirect genetic effects on offspring educational outcomes","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Cognitive Abilities and Testing","field":"Psychology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Norwegian Institute of Public Health; National Institutes of Health; Helse Vest; ZonMw; Jacobs Foundation; Sage Foundation; Helse- og Omsorgsdepartementet; Trond Mohn stiftelse; University of Texas at Austin; Stiftelsen Kristian Gerhard Jebsen; Universitetet i Bergen; Novo Nordisk; Novo Nordisk Fonden; Norges Forskningsråd; Canadian Institute for Advanced Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Nature versus nurture; Offspring; Educational attainment; Nuclear family; Norwegian; Inheritance (genetic algorithm); Developmental psychology; Affect (linguistics); Biology; Genetics; Psychology; Gene; Pregnancy; Sociology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003849271,0.0004907284,0.0005248695,0.0003048813,0.0002520194,0.0001240259,0.001038794,0.0003888725,0.008280995],"category_scores_gemma":[0.0009120695,0.0004573008,0.0001493322,0.0002255802,0.00004622465,0.00004886091,0.002542158,0.001799324,0.00006870597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003731255,"about_ca_system_score_gemma":0.0003360663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000668171,"about_ca_topic_score_gemma":0.0002453667,"domain_scores_codex":[0.996784,0.000317646,0.0003886581,0.001519587,0.0004898205,0.0005002724],"domain_scores_gemma":[0.9952034,0.002450668,0.000210214,0.001885814,0.00009217464,0.0001577687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007073973,0.002457214,0.7309406,0.001673189,0.004147116,0.0003674484,0.01717502,0.001373137,0.0002394729,0.02125865,0.06011652,0.1595442],"study_design_scores_gemma":[0.0006851711,0.0001480552,0.9851241,0.0002157103,0.0002418195,0.00002725934,0.002974726,0.0002557612,0.00002351216,0.00505985,0.004412272,0.0008318142],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9377007,0.001568963,0.0007014766,0.003205654,0.007033063,0.001693156,0.000532322,0.0001547053,0.04740993],"genre_scores_gemma":[0.9780048,0.000009010271,0.00652669,0.004891653,0.001240887,0.0001343163,0.0004262901,0.0001369062,0.008629502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2541834,"threshold_uncertainty_score":0.9997879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.125798897514358,"score_gpt":0.4053610700486456,"score_spread":0.2795621725342876,"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."}}