{"id":"W6938948278","doi":"10.60692/yaxxs-k8j13","title":"Predicting Malaria in a Highly Endemic Country using Environmental and Clinical Data Sources","year":2014,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Malaria Research and Control","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Malaria; Environmental data; Covariate; Predictive modelling; Public 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002991459,0.0004983214,0.0004378715,0.0009027386,0.0002127861,0.0007625264,0.0003179632,0.0003754022,0.0004890733],"category_scores_gemma":[0.01119151,0.0003159365,0.0003697666,0.001323276,0.0002131187,0.0007189021,0.0006929982,0.000658554,0.0001107983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005157251,"about_ca_system_score_gemma":0.0008182334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01909241,"about_ca_topic_score_gemma":0.02413449,"domain_scores_codex":[0.9990376,0.0006872426,0.00005314781,0.0001015847,0.00005300497,0.00006741895],"domain_scores_gemma":[0.9952999,0.003406281,0.0006808122,0.0001838671,0.0003031895,0.0001259052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002076995,0.00008159913,0.5880248,0.00005734408,0.0001980625,0.0001552383,0.0002087134,0.3900427,0.0004768138,0.0004225152,0.0007843776,0.01934006],"study_design_scores_gemma":[0.00003575682,0.0001666691,0.1682725,0.00006789246,0.00008769154,0.0001133742,0.0003838239,0.8271229,0.0005845447,0.00236313,0.000768426,0.00003331291],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864467,0.0002917584,0.01030591,0.0008059266,0.00001266163,0.00002289255,0.001587705,0.0000505089,0.0004757453],"genre_scores_gemma":[0.9954726,0.0001388714,0.003497209,0.00002654718,0.000007360127,0.000008777539,0.0007552808,0.000002985126,0.00009026098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01909241,"threshold_uncertainty_score":0.03796256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05178290210555543,"score_gpt":0.275654440698435,"score_spread":0.2238715385928796,"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."}}