{"id":"W2417168758","doi":"10.1038/srep40841","title":"Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks","year":2017,"lang":"en","type":"preprint","venue":"Scientific Reports","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Institute of Environmental Health Sciences; Intelligence Advanced Research Projects Activity; National Institutes of Health","keywords":"Outbreak; Infectious disease (medical specialty); Disease; Dengue fever; Disease surveillance; China; Geography; Incidence (geometry); Demography; Medicine; Environmental health; Pathology; Sociology","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":[0.007392324,0.00103001,0.0007912231,0.005676337,0.0004074233,0.001528823,0.0007855406,0.0009744592,0.001368174],"category_scores_gemma":[0.02625787,0.0004086496,0.001434775,0.004248283,0.0003486898,0.002025057,0.0007764968,0.001169316,0.0005405082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006125701,"about_ca_system_score_gemma":0.0006878282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005869586,"about_ca_topic_score_gemma":0.004837445,"domain_scores_codex":[0.9980764,0.0008950884,0.0002174949,0.000516417,0.0001974004,0.00009715235],"domain_scores_gemma":[0.9745222,0.02081467,0.00254673,0.0008293301,0.001011128,0.0002759325],"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":[0.001108092,0.0006624165,0.5051947,0.0007894507,0.00252756,0.0004219099,0.001529738,0.1897147,0.005617312,0.008783887,0.01010056,0.2735496],"study_design_scores_gemma":[0.00003798004,0.0001813935,0.07516272,0.00007196054,0.0003178699,0.0001816976,0.0003659455,0.9102498,0.001657193,0.008360618,0.003369249,0.00004357694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5329754,0.003559706,0.4467725,0.001393616,0.0002828481,0.0003246552,0.008916273,0.001669611,0.004105389],"genre_scores_gemma":[0.9242812,0.000926031,0.06400134,0.0001129283,0.0003796844,0.0003041589,0.008719033,0.0001103408,0.001165343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007392324,"threshold_uncertainty_score":0.03909481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0714903096583521,"score_gpt":0.3560032230490909,"score_spread":0.2845129133907388,"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."}}