{"id":"W4405892170","doi":"10.4103/apjtm.apjtm_673_24","title":"Using X Social Networks and web news mining to predict Marburg virus disease outbreaks","year":2024,"lang":"en","type":"article","venue":"Asian Pacific Journal of Tropical Medicine","topic":"Viral Infections and Outbreaks Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Outbreak; Case fatality rate; Contact tracing; Tanzania; Medicine; Disease; Marburg virus; Ebola virus; Environmental health; Geography; Socioeconomics; Virology; Infectious disease (medical specialty); Population; Coronavirus disease 2019 (COVID-19); Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008142634,0.00117963,0.000550752,0.008893435,0.0005188677,0.001560431,0.0005488147,0.0009440904,0.001496883],"category_scores_gemma":[0.003516329,0.0002298753,0.0009604508,0.002627678,0.0001873097,0.001417426,0.0008200309,0.0006626709,0.0008145514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005337941,"about_ca_system_score_gemma":0.0005859843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009074068,"about_ca_topic_score_gemma":0.01009548,"domain_scores_codex":[0.9992629,0.0001727587,0.000133889,0.0001982562,0.0001486604,0.00008359589],"domain_scores_gemma":[0.9979867,0.001138382,0.0004244157,0.000108669,0.0001622047,0.0001797546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001206421,0.001337,0.73178,0.001034772,0.001155676,0.00240129,0.0004490812,0.04111668,0.003286172,0.001906588,0.02250229,0.191824],"study_design_scores_gemma":[0.00008517421,0.0004834798,0.2488566,0.0002281413,0.000412266,0.001302632,0.001066049,0.7282781,0.001741186,0.004097581,0.01337699,0.00007172681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9243569,0.005058798,0.0165582,0.002037688,0.0004513665,0.0005189396,0.04191797,0.001813632,0.007286588],"genre_scores_gemma":[0.9417687,0.001599135,0.01760551,0.0001967164,0.000407259,0.0002233176,0.0365861,0.00003156251,0.001581693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009074068,"threshold_uncertainty_score":0.0180425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04048618964573544,"score_gpt":0.3498512980244295,"score_spread":0.3093651083786941,"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."}}