{"id":"W4403936360","doi":"10.1371/journal.pcbi.1012464","title":"Enhancing insights in sexually transmitted infection mapping: Syphilis in Forsyth County, North Carolina, a case study","year":2024,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases; National Institute on Minority Health and Health Disparities; National Institute of Allergy and Infectious Diseases; National Institutes of Health","keywords":"Outbreak; Syphilis; Geolocation; Geography; Demography; Congenital syphilis; Computer science; Medicine; Virology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009544861,0.0003297746,0.0001611404,0.001282993,0.001317182,0.0008187379,0.001009268,0.0005492153,0.001225585],"category_scores_gemma":[0.00612135,0.0001971613,0.0002650084,0.002027578,0.0004807001,0.0004022762,0.001048161,0.00065757,0.0001028593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003915067,"about_ca_system_score_gemma":0.003851278,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6741758,"about_ca_topic_score_gemma":0.8157739,"domain_scores_codex":[0.9992154,0.0004265569,0.00002554096,0.0000918901,0.000118043,0.0001226228],"domain_scores_gemma":[0.9979045,0.001179672,0.0002740164,0.000131333,0.0003887591,0.0001217201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001415811,0.0004366057,0.8542869,0.0003211129,0.000138307,0.009263362,0.02448682,0.0260068,0.002170068,0.002578361,0.009244661,0.07092538],"study_design_scores_gemma":[0.00004117283,0.000232596,0.7843916,0.0002770551,0.0001284869,0.001675946,0.08808047,0.1093346,0.002054291,0.001691864,0.01201107,0.00008083497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954305,0.00008984965,0.00125876,0.0006711953,0.000005875574,0.00007396599,0.0007209319,0.00002338884,0.001725494],"genre_scores_gemma":[0.9933901,0.0001379277,0.004861499,0.00009236507,0.000008198735,0.00006358689,0.0005865729,0.000008676156,0.0008511119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6741758,"threshold_uncertainty_score":0.6554861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.026429579091691,"score_gpt":0.3002190553907791,"score_spread":0.2737894762990881,"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."}}