{"id":"W1977165831","doi":"10.11599/germs.2012.1007","title":"The use of computational models to predict response to HIV therapy for clinical cases in Romania","year":2012,"lang":"en","type":"article","venue":"GERMS","topic":"HIV Research and Treatment","field":"Immunology and Microbiology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"AIDS Vancouver","funders":"National Institutes of Health; Università degli Studi di Brescia; Core Research for Evolutional Science and Technology; U.S. Department of Defense","keywords":"Antiretroviral therapy; Viral load; Receiver operating characteristic; Human immunodeficiency virus (HIV); Medicine; Statistics; Genotype; Area under the curve; Romanian; Internal medicine; Demography; Immunology; Mathematics; Biology","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":[0.002865901,0.0006900656,0.0006076122,0.0011578,0.0003312609,0.001050471,0.000798496,0.0005511782,0.001126502],"category_scores_gemma":[0.01060719,0.000390589,0.0008367458,0.0005828836,0.0003879579,0.0004721752,0.0007213194,0.0006229886,0.0002181826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001463471,"about_ca_system_score_gemma":0.001511193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02375951,"about_ca_topic_score_gemma":0.01359933,"domain_scores_codex":[0.9991066,0.0005812334,0.00006641939,0.0001123155,0.00006345234,0.00006995124],"domain_scores_gemma":[0.9955845,0.003401724,0.0003881041,0.0001775088,0.0003637222,0.00008441055],"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":[0.0002215877,0.00009780296,0.07501102,0.0001049311,0.0001924423,0.0002320806,0.0001179716,0.884286,0.0002830465,0.000859416,0.001290056,0.03730365],"study_design_scores_gemma":[0.00001872428,0.00005585965,0.006760073,0.00004720865,0.00002570354,0.00009350424,0.00005160983,0.9913688,0.0002204781,0.0008213575,0.0005256191,0.00001110612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9199424,0.001564942,0.06788022,0.002630289,0.00009238616,0.0002192852,0.001293161,0.0005147012,0.005862652],"genre_scores_gemma":[0.9765745,0.0003625705,0.02155766,0.0001310275,0.00002388474,0.000103591,0.0007879954,0.0000235,0.0004353002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02375951,"threshold_uncertainty_score":0.04724246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1717912089627714,"score_gpt":0.3924171450705108,"score_spread":0.2206259361077394,"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."}}