{"id":"W2901502410","doi":"10.2172/1481615","title":"Real-Time Automated Pathogen Identification by Enhanced Ribotyping (RAPIER) LDRD Final Report","year":2018,"lang":"en","type":"report","venue":"","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Laboratory Directed Research and Development; National Nuclear Security Administration; Oxford Nanopore Technologies; Sandia National Laboratories; U.S. Department of Energy","keywords":"Minion; Nanopore sequencing; Computer science; Identification (biology); Automation; Engineering; Biology; DNA sequencing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006768415,0.0004096417,0.0005331435,0.0001825362,0.0001097152,0.0001216854,0.0001688263,0.0007453022,0.0008284685],"category_scores_gemma":[0.0001896665,0.0003977277,0.0002222316,0.0003311329,0.00005966584,0.0001194954,0.00003631414,0.0003278856,0.0008182763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003974955,"about_ca_system_score_gemma":0.0001288434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001796972,"about_ca_topic_score_gemma":0.00001318451,"domain_scores_codex":[0.9972733,0.0000312225,0.001039162,0.0006027278,0.0006461649,0.0004073989],"domain_scores_gemma":[0.9984394,0.00003224508,0.0002933529,0.0006360736,0.0004576403,0.0001412339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004545231,0.00001999299,0.000003498486,0.0002002733,0.0001568152,0.00005027285,0.00001137379,0.00005764349,0.6214979,0.000002833088,0.3737912,0.00420365],"study_design_scores_gemma":[0.0004595811,0.0001444647,0.002468926,0.0007516064,0.0006596366,0.0009381715,0.00002515701,0.2703949,0.3561834,0.0001633499,0.3652479,0.002563005],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1017355,0.001115698,0.04761473,0.00013883,0.01214235,0.001695499,0.0006935649,0.02475348,0.8101103],"genre_scores_gemma":[0.4558415,0.01118745,0.004787525,0.00004201991,0.006994908,0.0002266596,0.01004432,0.0008511661,0.5100244],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.354106,"threshold_uncertainty_score":0.9999597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631487972736232,"score_gpt":0.2654652262001974,"score_spread":0.249150346472835,"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."}}