{"id":"W2940156422","doi":"10.2196/11036","title":"Identifying Key Topics Bearing Negative Sentiment on Twitter: Insights Concerning the 2015-2016 Zika Epidemic","year":2019,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sentiment analysis; Social media; Classifier (UML); Computer science; Topic model; Artificial intelligence; Information retrieval; Data science; 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":[0.001412936,0.0002956919,0.0006926283,0.0001427458,0.0003104609,0.0001386022,0.0002409002,0.00009960125,0.0001219876],"category_scores_gemma":[0.000459367,0.0002077762,0.0001034929,0.000335523,0.0001347299,0.0002330415,0.0001808204,0.0005171463,0.0002805904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002577773,"about_ca_system_score_gemma":0.0007458257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001718029,"about_ca_topic_score_gemma":0.0000665668,"domain_scores_codex":[0.996793,0.0005605266,0.0006275587,0.0006676097,0.0005539337,0.0007973612],"domain_scores_gemma":[0.9973987,0.0005194765,0.0003636564,0.0008036419,0.0001683876,0.0007461812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002677129,0.0001662247,0.9163113,0.0007549099,0.000176534,0.00004014716,0.005826418,0.00001145694,0.0001292983,0.001451477,0.04063709,0.03422743],"study_design_scores_gemma":[0.002196632,0.0003290686,0.5388259,0.0002570535,0.000002418525,0.00003528891,0.0009133356,0.001112135,0.00001241505,0.0001726785,0.4558144,0.0003287109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9510787,0.003532319,0.0002228363,0.03585685,0.0007914919,0.001949317,0.00005102966,0.0002225855,0.006294868],"genre_scores_gemma":[0.9832315,0.0008118695,0.0001911816,0.01185842,0.0004066129,0.00009448172,0.0001534932,0.00003937393,0.00321303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4151773,"threshold_uncertainty_score":0.8472867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05467089521911458,"score_gpt":0.3414452627004285,"score_spread":0.2867743674813139,"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."}}