{"id":"W4200401135","doi":"10.2196/32680","title":"An Evaluation of the Text Illness Monitoring (TIM) Platform for COVID-19: Cross-sectional Online Survey of Public Health Users","year":2021,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Cross-sectional study; Public health; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Public health surveillance; Medicine; Environmental health; Computer science; Virology; Outbreak; Nursing; Disease; Pathology; Infectious disease (medical specialty)","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":[0.01245557,0.000349923,0.0005101035,0.001419977,0.001017561,0.001835291,0.0008593373,0.0009414168,0.002705228],"category_scores_gemma":[0.02521667,0.0006031449,0.0008736445,0.00128332,0.0005429082,0.003519257,0.00205911,0.001228157,0.001012914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231949,"about_ca_system_score_gemma":0.001127596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00618244,"about_ca_topic_score_gemma":0.006640103,"domain_scores_codex":[0.9951782,0.002264414,0.000638683,0.0004424597,0.0009698001,0.0005063968],"domain_scores_gemma":[0.9812107,0.006418676,0.005937963,0.000863534,0.003402596,0.002166449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003827693,0.001783099,0.9709516,0.0003067179,0.00009025447,0.0001081919,0.007280792,0.0000840779,0.0002550501,0.00007021723,0.002656571,0.01603066],"study_design_scores_gemma":[0.00006910617,0.001655619,0.9795562,0.0001471618,0.00005491773,0.0002080876,0.01398413,0.00125576,0.0002059121,0.00004674129,0.002774604,0.00004172171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961914,0.000092576,0.0001927219,0.000279095,0.00001202493,0.0006507466,0.001383115,0.00001878823,0.001179531],"genre_scores_gemma":[0.9940685,0.0002404894,0.001259663,0.0006609979,0.00003119639,0.001699309,0.001476161,0.00001923901,0.0005443542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01245557,"threshold_uncertainty_score":0.06587213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2289364328060599,"score_gpt":0.4590881136434843,"score_spread":0.2301516808374245,"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."}}