{"id":"W3047279631","doi":"10.1109/icalt49669.2020.00049","title":"Analytics-oriented Preventive Care for Communicable Disease","year":2020,"lang":"en","type":"article","venue":"","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"","keywords":"Syphilis; Communicable disease; Analytics; Government (linguistics); Disease; Computer science; Predictive analytics; Medicine; Epidemiology; Epidemiological surveillance; Infectious disease (medical specialty); Outbreak; Environmental health; Data science; Internet privacy; Computer security; Public health; Immunology; Virology; Human immunodeficiency virus (HIV); Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004635194,0.0001124062,0.0002737094,0.00002478463,0.00006739372,0.00001156911,0.0001443739,0.00002375581,0.0004015582],"category_scores_gemma":[0.0004348076,0.00009755464,0.0001574852,0.0001795136,0.00005053602,0.00006561769,0.000123517,0.00007896107,0.00006612213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004500131,"about_ca_system_score_gemma":0.0001439907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001521093,"about_ca_topic_score_gemma":0.00002007291,"domain_scores_codex":[0.9991878,0.00003557498,0.0001751505,0.000244662,0.0001650925,0.0001917739],"domain_scores_gemma":[0.998597,0.00006952421,0.00004449015,0.0005213479,0.0002219053,0.0005457219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01112244,0.001490419,0.5085893,0.005489844,0.001531699,0.0003011053,0.004484275,0.0003318365,0.0009576491,0.01011275,0.4415479,0.01404077],"study_design_scores_gemma":[0.006973638,0.000614067,0.07682271,0.0001975804,0.0007771623,0.000001415219,0.003345477,0.02156361,0.0007172897,0.0001410718,0.8884133,0.0004326554],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4409508,0.01911395,0.1718002,0.09244568,0.001086106,0.02357578,0.02766013,0.005183863,0.2181835],"genre_scores_gemma":[0.9884689,0.00003109366,0.004282746,0.00325133,0.00009717465,0.00006072711,0.002122945,0.00002634841,0.001658741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5475181,"threshold_uncertainty_score":0.4396781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02747821114319854,"score_gpt":0.30657299272952,"score_spread":0.2790947815863215,"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."}}