{"id":"W4405508978","doi":"10.1007/s44202-024-00319-y","title":"Comparing US state resident IQ, socioeconomic status, and racial-ethnic composition as predictors of state violent crime rates","year":2024,"lang":"en","type":"article","venue":"Discover Psychology","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cape Breton University","funders":"","keywords":"Socioeconomic status; Ethnic group; Violent crime; Ethnic composition; Composition (language); Racial composition; State (computer science); Demography; Psychology; Criminology; Race (biology); Political science; Sociology; Mathematics; Population","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001406632,0.0002457837,0.0002460923,0.0008800258,0.000330119,0.0005023595,0.0002817476,0.000144248,0.001011299],"category_scores_gemma":[0.00498647,0.0001790988,0.0006179367,0.0007767203,0.0003391558,0.0003142435,0.0006721994,0.0003505624,0.0001347512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002177769,"about_ca_system_score_gemma":0.0005156123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03134367,"about_ca_topic_score_gemma":0.03971859,"domain_scores_codex":[0.9994341,0.0003166833,0.00003707987,0.00006131901,0.00007574877,0.00007506875],"domain_scores_gemma":[0.9978981,0.00095041,0.0005410825,0.0001881473,0.0002567938,0.0001654766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001724613,0.00001540764,0.9986217,0.000001701324,0.000060405,0.00001354357,0.00004400252,0.0002590029,0.00003877077,0.00005305561,0.00002747461,0.0008476585],"study_design_scores_gemma":[0.000001255348,0.00003167864,0.9976597,0.00000308509,0.00003510484,0.00002705275,0.0001289133,0.001910196,0.00007980986,0.00004837159,0.00007246452,0.00000234286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993787,0.00002231885,0.000194205,0.00001330091,0.000001652624,0.000002964428,0.00007975312,0.000004820777,0.0003022006],"genre_scores_gemma":[0.9996468,0.00001942444,0.00009508141,0.000003526106,0.000001912186,0.000003072021,0.0001478532,0.000001425067,0.00008092258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03134367,"threshold_uncertainty_score":0.06232244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04586033953626707,"score_gpt":0.4236058414238661,"score_spread":0.377745501887599,"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."}}