{"id":"W2883825770","doi":"10.2196/10834","title":"Characterizing Tweet Volume and Content About Common Health Conditions Across Pennsylvania: Retrospective Analysis","year":2018,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Volume (thermodynamics); Medicine","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":[0.001475005,0.000238298,0.0002681291,0.002405708,0.0006587963,0.0008650842,0.0003872058,0.0003649296,0.001817394],"category_scores_gemma":[0.01422166,0.0002978809,0.0002579036,0.002747963,0.0002715548,0.001362574,0.00126335,0.0006397375,0.0006986594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006072674,"about_ca_system_score_gemma":0.0005641123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01069606,"about_ca_topic_score_gemma":0.0118747,"domain_scores_codex":[0.9986156,0.000398988,0.0002272217,0.0003387874,0.0002738079,0.0001455901],"domain_scores_gemma":[0.9870359,0.005962962,0.003806986,0.0005999863,0.002163482,0.0004305984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002565068,0.00007780463,0.9663277,0.0003024078,0.0001398375,0.0002730599,0.004120421,0.0002390174,0.001484497,0.0002948677,0.009132156,0.01735173],"study_design_scores_gemma":[0.0000162287,0.0001784401,0.9709285,0.0001771504,0.0001651202,0.000531295,0.005963996,0.002787124,0.001961445,0.0003743128,0.0168811,0.00003517556],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639416,0.0004661576,0.00250467,0.0008974195,0.00004940159,0.0002574575,0.02965223,0.00008318257,0.002147954],"genre_scores_gemma":[0.9768152,0.0005965792,0.002657242,0.0004151858,0.00008988463,0.0007719991,0.01734626,0.0000352356,0.001272347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01069606,"threshold_uncertainty_score":0.02126759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04111159246956773,"score_gpt":0.3564484600302383,"score_spread":0.3153368675606705,"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."}}