{"id":"W3122100911","doi":"10.2139/ssrn.2518133","title":"Optimizing Tuberculosis Case Detection Through a Novel Diagnostic Device Placement Model: The Case of Uganda","year":2014,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Tuberculosis; Case finding; Medicine; Computer science; Business; Pathology","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":[0.002143165,0.0008229782,0.000718359,0.000805998,0.0008314977,0.002069963,0.001417599,0.001631598,0.001997709],"category_scores_gemma":[0.008106139,0.0005083132,0.00050339,0.0005799977,0.0006009652,0.001438891,0.001030501,0.0009205898,0.0004787835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001586328,"about_ca_system_score_gemma":0.002639584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01310936,"about_ca_topic_score_gemma":0.0126662,"domain_scores_codex":[0.998722,0.0006713826,0.00006246981,0.0002141944,0.0001400102,0.0001898139],"domain_scores_gemma":[0.9955147,0.002887847,0.0003287955,0.000263984,0.0007297874,0.0002748551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002600741,0.002026641,0.1162356,0.0003350708,0.000196292,0.003681543,0.001028337,0.6837646,0.01168039,0.008558461,0.005043928,0.1648483],"study_design_scores_gemma":[0.0000853401,0.0006479442,0.005960948,0.00003525393,0.00007836552,0.0005719549,0.0005765788,0.984165,0.002939436,0.003339184,0.001554371,0.00004556349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8544804,0.0005211143,0.1310573,0.003618332,0.0001348738,0.0005338404,0.0005001254,0.000749819,0.008404097],"genre_scores_gemma":[0.9545184,0.0001391868,0.04355428,0.0001229498,0.00002133797,0.0000734153,0.00009579051,0.00002194854,0.001452577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01310936,"threshold_uncertainty_score":0.02606612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100701324100297,"score_gpt":0.3017880863722895,"score_spread":0.2807810731312866,"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."}}