{"id":"W4230922212","doi":"10.21203/rs.2.17902/v1","title":"How to Optimally Estimate Malaria Readiness Indicators at the Health district Level? Findings from the Burkina Faso Service Availability and Readiness Assessment (SARA) Cross-Sectional Data","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Malaria Research and Control","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Malaria; Cross-sectional study; Environmental health; Service (business); Cross-sectional data; Geography; Medicine; Business; Statistics; Mathematics; Marketing","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":[0.00860739,0.0003415063,0.0003471618,0.001439315,0.0004030103,0.001218483,0.0006220879,0.0003669392,0.0008176168],"category_scores_gemma":[0.02372266,0.0002676047,0.0006613478,0.002498087,0.0002867649,0.0009346362,0.001002708,0.0004046925,0.0001683696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009206197,"about_ca_system_score_gemma":0.001044859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06010291,"about_ca_topic_score_gemma":0.05658,"domain_scores_codex":[0.9964918,0.002611433,0.0002197176,0.0002391435,0.0001885058,0.0002492996],"domain_scores_gemma":[0.9849848,0.01013756,0.002507028,0.0006396438,0.00136528,0.0003657756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003739347,0.00002625635,0.9892079,0.00004829706,0.00009298429,0.00003358988,0.0006885315,0.001390812,0.0001267333,0.0001141006,0.0002044557,0.008028864],"study_design_scores_gemma":[0.000009420093,0.0001382024,0.9823194,0.00007260956,0.000101771,0.00005393765,0.004441089,0.01128898,0.0003017029,0.000233848,0.001027498,0.00001162413],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959278,0.000207768,0.001888759,0.0002620629,0.000003489777,0.00006001342,0.001222975,0.00001036771,0.0004167885],"genre_scores_gemma":[0.9968534,0.00006674467,0.002154286,0.00002892351,0.000003429643,0.00005277536,0.0007502534,0.000002644219,0.00008752412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06010291,"threshold_uncertainty_score":0.1195061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07620317565102308,"score_gpt":0.381587366927672,"score_spread":0.3053841912766489,"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."}}