{"id":"W4388449009","doi":"10.1101/2023.11.06.23298167","title":"Regional variation and epidemiological insights in malaria underestimation in Cameroon","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Malaria Research and Control","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); York University","funders":"Los Alamos National Laboratory; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; International Development Research Centre; U.S. Department of Energy","keywords":"Malaria; Geography; Anopheles; Demography; Epidemiology; Environmental health; Biology; Veterinary medicine; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004414632,0.0003885479,0.0002615881,0.001275453,0.0003768665,0.0007404238,0.000366932,0.0002025799,0.001260382],"category_scores_gemma":[0.01058195,0.0002589691,0.0003300221,0.001950194,0.000527447,0.0006785012,0.0007327561,0.0004203024,0.00007826074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009917374,"about_ca_system_score_gemma":0.0006045711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05090311,"about_ca_topic_score_gemma":0.03681143,"domain_scores_codex":[0.9980123,0.001409203,0.0001015075,0.000227995,0.0000910377,0.0001579823],"domain_scores_gemma":[0.9952052,0.001992657,0.00167222,0.0004255948,0.0006010211,0.0001033415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006693001,0.00001452068,0.9870659,0.00002985216,0.00006307545,0.0001242661,0.000781627,0.005425484,0.0003759989,0.0005057134,0.0002750072,0.005271713],"study_design_scores_gemma":[0.000003982982,0.00002795778,0.9719189,0.00005939622,0.00003559838,0.000180594,0.001428661,0.0247312,0.0003203946,0.0004884316,0.0007871461,0.00001760593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956487,0.0002996785,0.002880491,0.0002334119,0.00000879956,0.00001962748,0.0004048939,0.00001127318,0.0004931852],"genre_scores_gemma":[0.9991543,0.00005376899,0.0006120675,0.00001368239,0.000002894103,0.000007001488,0.0001217452,0.000002417412,0.00003221686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05090311,"threshold_uncertainty_score":0.1012136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1040133088181166,"score_gpt":0.3492530387643117,"score_spread":0.2452397299461951,"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."}}