{"id":"W3003389116","doi":"10.3390/microorganisms8020196","title":"Evaluation of A Phylogenetic Pipeline to Examine Transmission Networks in A Canadian HIV Cohort","year":2020,"lang":"en","type":"article","venue":"Microorganisms","topic":"HIV Research and Treatment","field":"Immunology and Microbiology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Cumming School of Medicine, University of Calgary; Alberta Children's Hospital Research Institute; Canada Foundation for Innovation","keywords":"Transmission (telecommunications); Sanger sequencing; Inference; Confidence interval; Population; Phylogenetic tree; Biology; Pipeline (software); Medicine; Data mining; Genetics; Computer science; Computational biology; Artificial intelligence; DNA sequencing; Internal medicine; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007466397,0.001092125,0.0006279578,0.002007165,0.001937001,0.001040191,0.001877309,0.0007748628,0.002690775],"category_scores_gemma":[0.01787866,0.0006752043,0.001053689,0.001600541,0.0004328734,0.0005821685,0.001152275,0.001001604,0.0005089617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00631856,"about_ca_system_score_gemma":0.01236812,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6296839,"about_ca_topic_score_gemma":0.6508147,"domain_scores_codex":[0.998283,0.0006206929,0.00008243405,0.0004697961,0.0003512091,0.0001928841],"domain_scores_gemma":[0.9949086,0.00236237,0.0002724707,0.0005547286,0.001603462,0.0002983421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00159671,0.0003348199,0.4460394,0.0003216427,0.001034118,0.0005878055,0.001640994,0.2598149,0.00924351,0.004291536,0.01480453,0.26029],"study_design_scores_gemma":[0.0001430353,0.0002010928,0.06372734,0.00005302763,0.0002137242,0.0001932136,0.0004741604,0.9238083,0.003687057,0.002148642,0.005288844,0.00006164891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7840937,0.0008519649,0.181514,0.001904466,0.0001013033,0.001007105,0.01960704,0.006081438,0.004839002],"genre_scores_gemma":[0.8048332,0.0003282512,0.1787062,0.0002836786,0.00002440737,0.0002630689,0.01358157,0.0003158711,0.001663711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3703161,"threshold_uncertainty_score":0.744994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02171902782923727,"score_gpt":0.2591051584789282,"score_spread":0.2373861306496909,"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."}}