{"id":"W2307472195","doi":"10.1002/mgg3.212","title":"Genetics and genomic medicine in Mali: challenges and future perspectives","year":2016,"lang":"en","type":"article","venue":"Molecular Genetics & Genomic Medicine","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Human Genome Research Institute; Common Fund; National Institutes of Health","keywords":"Ethnic group; Population; Neglect; Health care; Economic growth; Landlocked country; Medicine; Geography; Socioeconomics; Political science; Sociology; Environmental health; Anthropology","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":[0.02894668,0.001190847,0.003931536,0.002707814,0.002952009,0.007066444,0.00328708,0.0127175,0.01036088],"category_scores_gemma":[0.02173858,0.0007199942,0.001353441,0.002864709,0.01024314,0.0177982,0.009606571,0.01624773,0.00191233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00561965,"about_ca_system_score_gemma":0.01795485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008036551,"about_ca_topic_score_gemma":0.01326499,"domain_scores_codex":[0.9941433,0.003068842,0.0005277954,0.0005298399,0.0009048613,0.0008252861],"domain_scores_gemma":[0.944952,0.03415376,0.002361174,0.001405349,0.007259119,0.009868654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006444211,0.0004408262,0.01474049,0.006492248,0.0004201213,0.00548793,0.003005484,0.002356461,0.001686315,0.1296438,0.2553904,0.5796915],"study_design_scores_gemma":[0.0001895369,0.0005689011,0.01623705,0.01355999,0.0003457701,0.01088875,0.01818183,0.002812044,0.0004358498,0.3641447,0.5721775,0.0004582108],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.001456238,0.407638,0.001513457,0.585016,0.002282818,0.00001194729,0.0001061733,0.00005004708,0.001925391],"genre_scores_gemma":[0.04926413,0.8164033,0.01192045,0.09118082,0.02905689,0.0001251204,0.0003692203,0.00004724609,0.001632816],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02894668,"threshold_uncertainty_score":0.1530865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008489204529563303,"score_gpt":0.2359682570888901,"score_spread":0.2274790525593268,"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."}}