{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000718912,0.0003640896,0.0002907316,0.001883924,0.00138935,0.0008237047,0.0006824895,0.0008640651,0.0008442642],"category_scores_gemma":[0.001747807,0.0002328953,0.0003298142,0.002968642,0.0007381226,0.001134908,0.001204094,0.0005042807,0.00009812915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001694511,"about_ca_system_score_gemma":0.001208545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1538874,"about_ca_topic_score_gemma":0.1901025,"domain_scores_codex":[0.9995381,0.000143775,0.00004194722,0.00006563499,0.00008422187,0.0001263399],"domain_scores_gemma":[0.9987098,0.0004988155,0.0003177054,0.00009747877,0.0001721009,0.0002040529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003759455,0.0001114507,0.9763998,0.00004821329,0.00005202847,0.005015473,0.010824,0.0003967171,0.0006256641,0.0003076208,0.0005115577,0.005669962],"study_design_scores_gemma":[0.000008586395,0.0001447245,0.9120638,0.00007492957,0.0001039686,0.004079594,0.07182476,0.007353059,0.0006603414,0.0004777062,0.003164153,0.00004445145],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988899,0.00007362879,0.0001459381,0.000208171,0.000003219256,0.00001579819,0.0002812744,0.000003662592,0.0003784178],"genre_scores_gemma":[0.9989696,0.000139973,0.0003737301,0.00003858182,0.00001070238,0.00001181849,0.0002321965,0.000002240261,0.0002212104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1538874,"threshold_uncertainty_score":0.3059833,"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."}}