{"id":"W7117700507","doi":"10.64539/sjcs.v1i1.2025.32","title":"Analysis of Suspected Factors in Tuberculosis Cases in Semarang City Using a Logistic Regression Model","year":2025,"lang":"","type":"article","venue":"Scientific Journal of Computer Science","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Logistic regression; Tuberculosis; Odds ratio; Statistic; Incidence (geometry); Descriptive statistics","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":[0.004260684,0.001160509,0.001479672,0.002924549,0.000628995,0.00229067,0.001599954,0.001194206,0.005094634],"category_scores_gemma":[0.01133399,0.0005792991,0.003481089,0.002430877,0.0003832607,0.0008216023,0.000921907,0.002329111,0.001181985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006157705,"about_ca_system_score_gemma":0.001413016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0154034,"about_ca_topic_score_gemma":0.005286777,"domain_scores_codex":[0.9978988,0.001012218,0.0002139817,0.0004638052,0.0001861825,0.0002249717],"domain_scores_gemma":[0.9922423,0.006012662,0.0007154971,0.000336554,0.0004695066,0.0002234999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006143087,0.0003687053,0.9698592,0.0001254402,0.0008735335,0.0008559041,0.000210199,0.01230095,0.0002704664,0.0003305761,0.001179825,0.01301083],"study_design_scores_gemma":[0.0001039918,0.0006151243,0.3615158,0.0002261456,0.001423424,0.001498359,0.001267495,0.6287794,0.0005745461,0.001208064,0.002703583,0.00008412344],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804226,0.001074789,0.01308933,0.0009457046,0.000159066,0.0001671294,0.002165805,0.0003106916,0.001664925],"genre_scores_gemma":[0.9924898,0.000364114,0.003947836,0.00005868189,0.00005957684,0.0001302665,0.00172089,0.00002945349,0.001199352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0154034,"threshold_uncertainty_score":0.03062749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1038577741520412,"score_gpt":0.4068287795732908,"score_spread":0.3029710054212496,"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."}}