{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00113976,0.0003245168,0.0007863338,0.0001938467,0.0001689213,0.0000772733,0.0001099869,0.0003448373,0.0001438922],"category_scores_gemma":[0.002553888,0.0001935673,0.0002670844,0.0001361591,0.0001652376,0.00008168506,0.00008188828,0.0008319314,0.000001684027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004709074,"about_ca_system_score_gemma":0.00044752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003733962,"about_ca_topic_score_gemma":0.004717595,"domain_scores_codex":[0.9967566,0.0001933994,0.0006465745,0.0003954684,0.001421938,0.0005860649],"domain_scores_gemma":[0.9975221,0.00112124,0.0005778963,0.0004606165,0.0001547327,0.000163452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01525142,0.002329498,0.3831848,0.002846038,0.03146181,0.003460816,0.001961724,0.0001048301,0.02812733,0.000203222,0.06524559,0.4658229],"study_design_scores_gemma":[0.02347407,0.002336393,0.8373596,0.003811916,0.003763581,0.0002438555,0.001958454,0.03162281,0.002052781,0.0001322611,0.09173189,0.001512361],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8759236,0.004107098,0.05739195,0.002917361,0.001968907,0.02516522,0.006240829,0.000375302,0.02590973],"genre_scores_gemma":[0.9478642,0.002578849,0.002487355,0.00002373222,0.0001827586,0.000005641277,0.001088105,0.0001362751,0.04563311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4643105,"threshold_uncertainty_score":0.7893445,"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."}}