{"id":"W4391328060","doi":"10.2139/ssrn.4706370","title":"Bringing TB Genomics to the Clinic: A Comprehensive Pipeline to Predict Antimicrobial Susceptibility from Genomic Data, Validated and Accredited to ISO Standards","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Accreditation; Genomics; Pipeline (software); Medicine; Genomic medicine; Family medicine; Computational biology; Biology; Genetics; Computer science; Medical education; Genome; Gene","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":[0.01017198,0.002157335,0.002450048,0.006948585,0.0008465713,0.006408847,0.001821636,0.001817867,0.0108935],"category_scores_gemma":[0.03236513,0.001506942,0.002016342,0.003400844,0.0006345456,0.003094107,0.005214817,0.003381652,0.01669821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008921933,"about_ca_system_score_gemma":0.004805523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002709043,"about_ca_topic_score_gemma":0.003474025,"domain_scores_codex":[0.994131,0.001282299,0.000646109,0.001300471,0.002298729,0.0003413027],"domain_scores_gemma":[0.9841797,0.006317832,0.001425958,0.003490845,0.003510861,0.001074654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001680369,0.0007106479,0.03625125,0.003207737,0.0009198503,0.001212372,0.002044742,0.006227699,0.08428158,0.005584878,0.2428382,0.6150407],"study_design_scores_gemma":[0.0006803597,0.001258319,0.08302558,0.002371984,0.001218855,0.003372838,0.001970119,0.09073646,0.1602486,0.07520738,0.5789448,0.0009647017],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0296091,0.00517093,0.6100014,0.007736987,0.0007907256,0.0020821,0.1018888,0.2312436,0.0114764],"genre_scores_gemma":[0.09130457,0.00379887,0.7476593,0.003339781,0.0006587252,0.001279596,0.1285152,0.01700342,0.00644058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0108935,"threshold_uncertainty_score":0.05379522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02655515976516378,"score_gpt":0.3118755212032846,"score_spread":0.2853203614381208,"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."}}