{"id":"W2047420328","doi":"10.1007/s10464-009-9263-7","title":"Area‐Based Socioeconomic Characteristics of Industries at High Risk for Violence in the Workplace","year":2009,"lang":"en","type":"article","venue":"American Journal of Community Psychology","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute for Occupational Safety and Health; University of North Carolina at Chapel Hill; Centers for Disease Control and Prevention","keywords":"Socioeconomic status; Poverty; Context (archaeology); Poison control; Human capital; Socioeconomics; Demographic economics; Geography; Environmental health; Demography; Psychology; Sociology; Economics; Economic growth; Population; Medicine","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":[0.0002592094,0.00009529915,0.0001340796,0.0008770369,0.0003829594,0.0003910079,0.000164052,0.0001669531,0.002230078],"category_scores_gemma":[0.001617642,0.00010981,0.0001507392,0.0005392159,0.0001666984,0.000208007,0.0005734073,0.0001692398,0.0002124522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001660291,"about_ca_system_score_gemma":0.0002138776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00973718,"about_ca_topic_score_gemma":0.02145204,"domain_scores_codex":[0.9997659,0.00006573177,0.00002159981,0.00003014751,0.00005678849,0.00005994034],"domain_scores_gemma":[0.9989445,0.0001244771,0.0005036296,0.00004916054,0.0001316666,0.0002465716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001525228,0.00002272553,0.9985484,0.000002529385,0.00001196087,0.00004636401,0.000129028,0.00003717181,0.0001380737,0.00001864135,0.00003109573,0.0009986678],"study_design_scores_gemma":[4.415143e-7,0.00001823836,0.9995189,0.0000023257,0.00000212264,0.00004262442,0.0002910779,0.00005441393,0.00001259366,0.00001131407,0.00004521483,8.741142e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996176,0.00002279651,0.00003174199,0.00001065884,6.638729e-7,0.000001575091,0.0000450251,4.45838e-7,0.0002694261],"genre_scores_gemma":[0.9998201,0.00001790521,0.00002664589,0.000003126567,0.000001070971,0.00000138451,0.00004736364,3.314784e-7,0.00008208427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00973718,"threshold_uncertainty_score":0.01936102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06145317210029919,"score_gpt":0.4017265136313014,"score_spread":0.3402733415310021,"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."}}