{"id":"W2966084642","doi":"10.1038/s41598-019-47857-3","title":"Real-Time Selective Sequencing with RUBRIC: Read Until with Basecall and Reference-Informed Criteria","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Laboratory Directed Research and Development; National Nuclear Security Administration; University of Nottingham; Sandia National Laboratories; U.S. Department of Energy","keywords":"Rubric; Computer science; Computational biology; Information retrieval; Data mining; Data science; Biology; Psychology; Mathematics education","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":[0.008780478,0.002002825,0.002234724,0.00164167,0.001383702,0.002252519,0.003092257,0.001859469,0.004889302],"category_scores_gemma":[0.02241819,0.001308003,0.001414677,0.001523427,0.001641294,0.001506498,0.002045711,0.002515955,0.005039978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001167342,"about_ca_system_score_gemma":0.002815501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002899675,"about_ca_topic_score_gemma":0.007926152,"domain_scores_codex":[0.989899,0.002730038,0.000715533,0.003237837,0.002959542,0.0004579835],"domain_scores_gemma":[0.9870502,0.004983297,0.001807469,0.003253096,0.002390347,0.0005155297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002660582,0.0004458781,0.01291335,0.002112288,0.0008760168,0.000561532,0.001636818,0.04033711,0.5664377,0.01455987,0.02219787,0.3352609],"study_design_scores_gemma":[0.0001000132,0.000459983,0.003506607,0.0001150761,0.0001121741,0.0006611477,0.0001263353,0.2888009,0.6751896,0.006458901,0.02407758,0.0003915858],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03752742,0.0006519447,0.9301015,0.0001189793,0.00009962024,0.0003606838,0.001363854,0.02772372,0.002052316],"genre_scores_gemma":[0.0976003,0.0002289974,0.8907136,0.0002907844,0.00003223564,0.0006676186,0.002367861,0.005378002,0.002720572],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008780478,"threshold_uncertainty_score":0.04643619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01143604767143263,"score_gpt":0.2384513074241399,"score_spread":0.2270152597527073,"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."}}