{"id":"W2794578899","doi":"10.2196/10637","title":"Descriptive Analysis of Malaria Surveillance System Data, Yemen, 2011-2015","year":2018,"lang":"en","type":"article","venue":"Iproceedings","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Malaria; Environmental health; Population; Descriptive statistics; Medicine; Geography; Medical emergency; Immunology; Statistics","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":[0.002479753,0.0005539086,0.0005070437,0.003773419,0.0003372256,0.0005764373,0.0005619354,0.0002061853,0.00407694],"category_scores_gemma":[0.008433719,0.0002664596,0.0007041741,0.006936539,0.0002433774,0.0006632401,0.0006630597,0.0003704414,0.0005707404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0021891,"about_ca_system_score_gemma":0.001974147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03869219,"about_ca_topic_score_gemma":0.02407844,"domain_scores_codex":[0.9981303,0.0004527295,0.0004997342,0.000351815,0.0002630758,0.0003023725],"domain_scores_gemma":[0.9959682,0.0008392124,0.0020146,0.0002488096,0.0008091161,0.0001200048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003652537,0.00003279643,0.9730181,0.0004929508,0.0004829928,0.0001315692,0.0003036258,0.001469217,0.0001332484,0.0002232436,0.01650151,0.006845488],"study_design_scores_gemma":[0.00002927882,0.0001100124,0.9914557,0.0001457614,0.00009588242,0.0001891352,0.0006828776,0.001331248,0.000197019,0.00006203335,0.005681742,0.00001912268],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.497383,0.001100811,0.001088275,0.0002309881,0.0000317204,0.0003822025,0.4977439,0.0001747804,0.001864228],"genre_scores_gemma":[0.7676208,0.0005916459,0.001232263,0.00009769449,0.00002649418,0.001542034,0.2280205,0.00003185912,0.0008365798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03869219,"threshold_uncertainty_score":0.07693392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03195139341270733,"score_gpt":0.3010513459949365,"score_spread":0.2690999525822292,"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."}}