{"id":"W1980590900","doi":"10.1503/cmaj.080669","title":"Unravelling the contributions of social, environmental and genetic factors to health differences","year":2008,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; National Human Genome Research Institute; U.S. Department of Health and Human Services","keywords":"Ethnic group; Data science; Computer science; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005763446,0.0008300996,0.002111414,0.0009137365,0.002720578,0.002758203,0.002012438,0.02128526,0.004125375],"category_scores_gemma":[0.01791165,0.0006049861,0.0009779456,0.0007490198,0.007558657,0.008447544,0.002089342,0.03457604,0.001973058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002936652,"about_ca_system_score_gemma":0.003021514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008892747,"about_ca_topic_score_gemma":0.01483881,"domain_scores_codex":[0.9961722,0.001845836,0.0004128524,0.000450676,0.0008412665,0.0002771283],"domain_scores_gemma":[0.979887,0.01572246,0.000805734,0.0005875733,0.001996246,0.00100099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003248491,0.0003165631,0.02861297,0.000749713,0.0002263355,0.01440892,0.003320255,0.0005034495,0.00183619,0.02343481,0.714232,0.2120339],"study_design_scores_gemma":[0.0003584306,0.0004015611,0.02990486,0.001758525,0.0002514732,0.02561655,0.009266807,0.00277421,0.001035629,0.2170545,0.711264,0.0003134818],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001838196,0.01075628,0.000491567,0.9810249,0.004557207,0.000007001182,0.00002339717,0.00002027774,0.001281359],"genre_scores_gemma":[0.03103377,0.02629506,0.002450137,0.8544952,0.08228899,0.00004104661,0.0000359203,0.00002354606,0.003336391],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02128526,"threshold_uncertainty_score":0.03048038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00716912178406838,"score_gpt":0.2219832446443122,"score_spread":0.2148141228602439,"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."}}