{"id":"W6922226003","doi":"10.11575/prism/49505","title":"Racialized Communities, Equity and Precision Medicine in Canada","year":2023,"lang":"en","type":"other","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precision medicine; Genomics; Equity (law); Health equity; Context (archaeology); Human genetics; Health care; Corporate governance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.009174338,0.0003171318,0.0006113336,0.00100577,0.03512062,0.008711842,0.002630298,0.007636487,0.00842341],"category_scores_gemma":[0.02216192,0.0002946946,0.0006971084,0.00210666,0.01998736,0.003222996,0.007878667,0.009601759,0.0003581499],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09233809,"about_ca_system_score_gemma":0.2992148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9800026,"about_ca_topic_score_gemma":0.9879196,"domain_scores_codex":[0.9897813,0.00253829,0.0003107158,0.0008593063,0.00354156,0.002968927],"domain_scores_gemma":[0.9861626,0.004328497,0.0005743727,0.000439734,0.004022148,0.004472573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005875572,0.0000439516,0.007141395,0.0004145397,0.00005139007,0.001211535,0.05829893,0.0003557116,0.0003036554,0.6156626,0.2341663,0.08229111],"study_design_scores_gemma":[0.00004918877,0.00002681966,0.01172706,0.002041894,0.00007627339,0.0004685578,0.05515823,0.0004441554,0.0003941154,0.1178064,0.8116583,0.000149008],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01793027,0.02560379,0.001175155,0.8146996,0.003695508,0.00008128074,0.0002093316,0.00002996743,0.136575],"genre_scores_gemma":[0.5022484,0.0292371,0.002490809,0.4081249,0.001669226,0.0001548157,0.0001464951,0.00009260933,0.05583557],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9973697,"threshold_uncertainty_score":0.6699628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1191277855392408,"score_gpt":0.3917904478818729,"score_spread":0.2726626623426321,"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."}}