{"id":"W3018690985","doi":"10.3389/fpubh.2020.00111","title":"Indigenous Genomic Databases: Pragmatic Considerations and Cultural Contexts","year":2020,"lang":"en","type":"article","venue":"Frontiers in Public Health","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia; University of British Columbia; BC Cancer Agency","funders":"","keywords":"Indigenous; Public health; Perspective (graphical); Front (military); Political science; Data science; Public relations; Medicine; Geography; Computer science; Biology; Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003488604,0.0001297283,0.0002205204,0.00003047478,0.0002082511,0.0000658855,0.0001000894,0.00008197633,0.000009366775],"category_scores_gemma":[0.0002795599,0.0001295999,0.0000373883,0.00008017569,0.0001395893,0.00001201681,0.00008542962,0.0001352277,0.000002986994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005011693,"about_ca_system_score_gemma":0.00068613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005987531,"about_ca_topic_score_gemma":0.00008808954,"domain_scores_codex":[0.9987181,0.0001672202,0.0002978945,0.0003581647,0.0000922652,0.0003663481],"domain_scores_gemma":[0.9993023,0.00001130488,0.00009777961,0.0002142895,0.00005003784,0.0003243293],"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":[0.00004741065,0.00027127,0.196935,0.0004642507,0.0003066239,0.00001638755,0.05494118,0.00009014376,0.01022545,0.001370761,0.7070774,0.0282541],"study_design_scores_gemma":[0.003632272,0.0009071563,0.05425819,0.000035298,0.00002164836,0.00006360528,0.02009839,0.001832126,0.0006958211,0.0005966303,0.9169804,0.000878454],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9474114,0.01239305,0.02071062,0.0175276,0.0004602055,0.0008030773,0.0001938283,0.00003060416,0.0004695723],"genre_scores_gemma":[0.9655666,0.003417567,0.01915314,0.01112316,0.0002152084,0.00002516387,0.0003930618,0.00001885178,0.0000872806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.209903,"threshold_uncertainty_score":0.5284929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02911462815053318,"score_gpt":0.2873320631513497,"score_spread":0.2582174350008165,"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."}}