{"id":"W1964216735","doi":"10.1186/1471-2458-13-606","title":"Screen more or screen more often? Using mathematical models to inform syphilis control strategies","year":2013,"lang":"en","type":"article","venue":"BMC Public Health","topic":"Syphilis Diagnosis and Treatment","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Public Health Ontario; University of Toronto","funders":"Canadian Institutes of Health Research; University of Toronto","keywords":"Syphilis; Medicine; Population; Incidence (geometry); Biostatistics; Epidemiology; Latent Syphilis; Demography; Transmission (telecommunications); Public health; Environmental health; Immunology; Internal medicine; Telecommunications; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006888533,0.0003664416,0.0009217059,0.0003100787,0.0002367346,0.0002801254,0.0002213602,0.0001637014,0.0008950005],"category_scores_gemma":[0.0002762422,0.0002409839,0.00016837,0.0005261101,0.0001080416,0.0009013426,0.00009386471,0.0002110897,0.0002252591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005366109,"about_ca_system_score_gemma":0.002501273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004677948,"about_ca_topic_score_gemma":0.0002699895,"domain_scores_codex":[0.9968257,0.00007853084,0.0008654807,0.0004546011,0.0007587879,0.0010169],"domain_scores_gemma":[0.9969404,0.0002571473,0.0001902199,0.0007562531,0.000378953,0.001477054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001948706,0.01689973,0.1440742,0.007789017,0.003856958,0.0003729638,0.04437653,0.007919144,0.0001548449,0.2885826,0.1562968,0.3277284],"study_design_scores_gemma":[0.02707309,0.005696759,0.4550867,0.002422926,0.000540227,0.0008520414,0.04022618,0.4404235,0.00005341644,0.01006622,0.01546105,0.002097858],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7791612,0.0006292775,0.05187906,0.1540169,0.0001102772,0.008013542,0.0002740319,0.0004707725,0.005444963],"genre_scores_gemma":[0.9621508,0.00003339491,0.02063747,0.01604286,0.0002537589,0.0004039041,0.0001042424,0.00006405864,0.000309578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4325044,"threshold_uncertainty_score":0.9827037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1640732146064067,"score_gpt":0.382105511443903,"score_spread":0.2180322968374964,"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."}}