{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001961665,0.0003404078,0.001460609,0.0002591995,0.0008543475,0.0002087153,0.0001550288,0.0001172691,0.0001411855],"category_scores_gemma":[0.0003635865,0.0003207686,0.000141183,0.001092569,0.0006177711,0.0003246147,0.0001633995,0.0003693996,0.00003967652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003677364,"about_ca_system_score_gemma":0.0007175134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009096556,"about_ca_topic_score_gemma":0.004196352,"domain_scores_codex":[0.9961045,0.0004854878,0.0008509584,0.0008777447,0.0004502825,0.001231053],"domain_scores_gemma":[0.9960746,0.000123917,0.000540821,0.0007497524,0.0004959586,0.002014966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009748204,0.0001501919,0.9816885,0.000245038,0.0002771029,0.00001100682,0.001484385,3.923615e-8,0.00003519016,0.0001804012,0.00650204,0.009328631],"study_design_scores_gemma":[0.001377067,0.0007177321,0.9246792,0.00003866227,0.000006070414,0.00004034387,0.0006952265,0.0004195448,7.224739e-7,0.00001352735,0.07176872,0.0002431708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637372,0.00179792,0.0002380317,0.02893458,0.0002383837,0.001143463,0.003105968,0.0002662704,0.000538159],"genre_scores_gemma":[0.9823207,0.001052956,0.0001423314,0.01359137,0.0003233018,0.0001159903,0.002025305,0.00003718688,0.0003908216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06526668,"threshold_uncertainty_score":0.9999244,"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."}}