{"id":"W2951345899","doi":"10.1038/d41586-019-01885-1","title":"Build science in Africa","year":2019,"lang":"en","type":"article","venue":"Nature","topic":"Global Health and Surgery","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Climate change; Population growth; Population; Geography; Political science; Ecology; Medicine; Biology; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002848869,0.00003482114,0.00008860301,0.00009766717,0.00001588179,0.000003868856,0.00005463515,0.0002770399,0.0001026293],"category_scores_gemma":[0.0001552156,0.00002613005,0.00001664028,0.0005109629,0.00002660038,0.0000390813,0.0000152425,0.0009036139,0.0001755378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005712184,"about_ca_system_score_gemma":0.0002302849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009297009,"about_ca_topic_score_gemma":0.000002801681,"domain_scores_codex":[0.999324,0.000004468128,0.0000619596,0.0001227941,0.0002251512,0.0002616216],"domain_scores_gemma":[0.9996756,0.00002084212,0.00001067522,0.0001370729,0.00004499274,0.0001107883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002149273,0.0001245351,0.9126138,0.0001814651,0.000001981447,0.0001200839,0.0002402998,0.000002246103,0.006486882,0.006702813,0.06271972,0.01059127],"study_design_scores_gemma":[0.0004981218,0.00005750513,0.649834,0.00008582727,0.000001788381,0.00002297712,0.00004837687,0.0000820978,0.0003861361,0.0002340795,0.3486963,0.0000528037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8897038,0.001089388,2.697493e-7,0.00255929,0.0005485656,0.0001127897,0.000001003776,0.00001555059,0.1059694],"genre_scores_gemma":[0.9940091,0.00001218979,0.0001422755,0.003947272,0.00004207753,0.000001070732,0.000001030647,0.000002322464,0.001842708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2859766,"threshold_uncertainty_score":0.3925803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008245464488520779,"score_gpt":0.3037173382855378,"score_spread":0.295471873797017,"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."}}