{"id":"W2942914173","doi":"10.1139/geomat-2018-0016","title":"Space, time, and disease on social media: a case study of dengue fever in China","year":2018,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Social media; Event (particle physics); Data science; Computer science; China; Space (punctuation); Process (computing); Diffusion; Geography; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001855905,0.0001199058,0.0003181571,0.0001134434,0.00005300247,0.000007940131,0.00005602583,0.00002829658,0.0002859896],"category_scores_gemma":[0.000738533,0.000101941,0.00003002352,0.0001870019,0.0001412366,0.00004420751,0.00007657331,0.0000852518,0.0001105103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002506684,"about_ca_system_score_gemma":0.0000733299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001293081,"about_ca_topic_score_gemma":0.0004295944,"domain_scores_codex":[0.9990222,0.0000933136,0.0002261753,0.0002192524,0.0002588926,0.0001801261],"domain_scores_gemma":[0.9992102,0.0001188852,0.00006641732,0.0003130507,0.00004729719,0.0002440937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002369801,0.01407769,0.8025853,0.001218848,0.0005719027,0.05425171,0.0450967,0.000005964697,0.0005870775,0.0004261617,0.05877453,0.02003431],"study_design_scores_gemma":[0.003015469,0.000187698,0.9946008,0.00009383803,0.0001138429,0.0001087418,0.0009338816,0.000537061,0.00001578072,0.0001679144,0.0001084448,0.0001165709],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982981,0.00003360533,0.000002091283,0.0003100197,0.00004438465,0.0004851964,0.0001331154,0.00003559517,0.000657869],"genre_scores_gemma":[0.9995157,0.000002083361,0.0001009893,0.00009002724,0.0001504016,0.00001778908,0.00002781006,0.00001590625,0.0000793407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1920154,"threshold_uncertainty_score":0.4157034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01480143842174555,"score_gpt":0.2850278032329554,"score_spread":0.2702263648112099,"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."}}