{"id":"W3005429949","doi":"10.2196/11512","title":"Cluster Detection Mechanisms for Syndromic Surveillance Systems: Systematic Review and Framework Development","year":2020,"lang":"en","type":"review","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scopus; Disease surveillance; Cluster analysis; Systematic review; Data mining; Data science; MEDLINE; Medicine; Disease; Machine learning; Pathology","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":[0.004563243,0.001114205,0.009221047,0.0003243074,0.0003848322,0.0002596859,0.0003896817,0.0005841806,0.00001199819],"category_scores_gemma":[0.003705474,0.0008903435,0.0004193168,0.000862862,0.0001075761,0.0001669576,0.0002458552,0.000800039,0.00006391195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007004263,"about_ca_system_score_gemma":0.003037342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001091156,"about_ca_topic_score_gemma":0.00003459282,"domain_scores_codex":[0.9917063,0.001751459,0.002995425,0.001638837,0.0006668627,0.00124118],"domain_scores_gemma":[0.9930144,0.00145162,0.001881669,0.00119025,0.0003892015,0.002072838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002361555,0.00004879237,0.00004011335,0.899363,0.0004013164,0.00001489076,0.00005733124,2.292955e-8,2.653509e-8,0.0001724728,0.001349207,0.09852923],"study_design_scores_gemma":[0.000566291,0.0002747111,0.00006277738,0.1986715,0.0001239708,0.0007820267,0.0000342859,0.00007600097,9.480758e-9,0.00001352623,0.7986741,0.0007207984],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000003285352,0.9645641,0.01080372,0.001638133,0.0005008071,0.02127295,0.0007900523,0.000392264,0.00003462897],"genre_scores_gemma":[0.0001998021,0.9851062,0.001462525,0.003637601,0.0002038445,0.007643088,0.00137692,0.0001977423,0.0001722722],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7973249,"threshold_uncertainty_score":0.9993547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0458739249753697,"score_gpt":0.3477040022694526,"score_spread":0.301830077294083,"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."}}