{"id":"W2945392980","doi":"10.2196/12383","title":"Flu Outbreak Prediction Using Twitter Posts Classification and Linear Regression With Historical Centers for Disease Control and Prevention Reports: Prediction Framework Study","year":2019,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outbreak; Computer science; Social media; Control (management); Resource (disambiguation); Disease control; Disease; Disease surveillance; Internet privacy; Machine learning; Data science; Data mining; Environmental health; Artificial intelligence; Medicine; World Wide Web; Virology; Pathology","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":[0.002655497,0.001062782,0.0007245761,0.001840536,0.0004095841,0.0008764167,0.001066662,0.0008231535,0.001683048],"category_scores_gemma":[0.004734326,0.0003557174,0.001133378,0.00111351,0.0003238076,0.001175981,0.0006612073,0.00112612,0.0005096569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001282555,"about_ca_system_score_gemma":0.0009779391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02865439,"about_ca_topic_score_gemma":0.01651883,"domain_scores_codex":[0.9992228,0.0002494118,0.00004250451,0.0002718856,0.000113494,0.00009992788],"domain_scores_gemma":[0.9980934,0.001133825,0.0002509077,0.0000737568,0.0003609093,0.00008713065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005155738,0.000985335,0.1227793,0.0001832433,0.0005245297,0.0003621834,0.0002160996,0.6960055,0.00172379,0.005396259,0.005421023,0.1658872],"study_design_scores_gemma":[0.00000371067,0.00002486267,0.002022943,0.000004250273,0.00001248524,0.00001247564,0.00001287479,0.9972622,0.0001448062,0.0003505899,0.0001450954,0.000003724757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5144951,0.001275212,0.4732131,0.002321192,0.0001441271,0.0003718867,0.001989576,0.001887688,0.004302118],"genre_scores_gemma":[0.9327861,0.0003877785,0.06272553,0.0000878683,0.0001562042,0.0001800137,0.001376625,0.00003324232,0.002266642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02865439,"threshold_uncertainty_score":0.05697525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03905220092828261,"score_gpt":0.3329857680524992,"score_spread":0.2939335671242166,"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."}}