{"id":"W2342866717","doi":"10.4095/219902","title":"The Use of Radar Remote Sensing for Identifying Environmental Factors Associated with Malaria Risk in Coastal Kenya","year":2002,"lang":"en","type":"report","venue":"","topic":"Malaria Research and Control","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Malaria; Remote sensing; Radar; Geography; Environmental science; Environmental health; Environmental resource management; Computer science; Medicine; Telecommunications; Immunology","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":[0.0003475343,0.0002374079,0.0001391183,0.00111852,0.0002466135,0.0003526905,0.0001715999,0.0001614959,0.0007257392],"category_scores_gemma":[0.0009482354,0.0001328834,0.0001132102,0.0006410119,0.0001240654,0.0002415714,0.0002092074,0.0001174141,0.0001512883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002908949,"about_ca_system_score_gemma":0.0003229604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02516034,"about_ca_topic_score_gemma":0.04973622,"domain_scores_codex":[0.9998782,0.00005926409,0.00000986447,0.00001650866,0.00002363603,0.00001260343],"domain_scores_gemma":[0.9998093,0.00008096268,0.00005268649,0.000006388848,0.0000355247,0.00001510863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002061865,0.000241512,0.8181754,0.0003261972,0.00008115279,0.0009827596,0.001216581,0.003146221,0.01865736,0.000357868,0.001049085,0.1555598],"study_design_scores_gemma":[0.00001368409,0.0002359698,0.9865322,0.00009441146,0.00005255806,0.00045667,0.001926494,0.007411236,0.00143034,0.0001008345,0.001721856,0.00002382979],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914231,0.001260507,0.001460961,0.0002026383,0.00000860911,0.0001125678,0.0004614616,0.00001826188,0.005051906],"genre_scores_gemma":[0.9841167,0.001548493,0.01285597,0.00004486661,0.00001070513,0.00005398544,0.0003027652,0.000002947254,0.00106363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02516034,"threshold_uncertainty_score":0.05002779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0891274697005113,"score_gpt":0.301667181480424,"score_spread":0.2125397117799127,"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."}}