{"id":"W2980787671","doi":"10.1101/808410","title":"Accurate and Complete Genomes from Metagenomes","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Biological and Environmental Research; Office of Science; National Institutes of Health; Innovative Genomics Institute; Genome Canada; University of California Berkeley; U.S. Department of Energy","keywords":"Genome; Metagenomics; Bacterial genome size; Biology; Computational biology; Genomics; Shotgun sequencing; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002670969,0.0009705389,0.001030518,0.002861539,0.0006648425,0.002282938,0.001061574,0.001317017,0.001849647],"category_scores_gemma":[0.008371954,0.0007072059,0.0009184863,0.003350198,0.0005304706,0.002191957,0.00178685,0.002123144,0.001927977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008492477,"about_ca_system_score_gemma":0.001080281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001075313,"about_ca_topic_score_gemma":0.001854031,"domain_scores_codex":[0.9975776,0.0004724863,0.0002412551,0.0005059431,0.00102377,0.0001789511],"domain_scores_gemma":[0.9955999,0.0008122535,0.0006335231,0.001260761,0.001405932,0.0002876641],"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":[0.0008554145,0.0001194061,0.01241877,0.002109792,0.0003829944,0.0004351553,0.0006373722,0.007647041,0.8806579,0.00755567,0.004809136,0.08237135],"study_design_scores_gemma":[0.00009467459,0.000564185,0.07160898,0.0009223449,0.0006071518,0.002015104,0.0007027683,0.03303066,0.6528205,0.01924432,0.2181682,0.0002211172],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5428441,0.02365109,0.3457665,0.001674425,0.0008818033,0.0003812276,0.07342393,0.004668997,0.006707882],"genre_scores_gemma":[0.4278925,0.007630263,0.4211019,0.0006814309,0.0002004228,0.0002682261,0.1382097,0.00196604,0.002049516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002861539,"threshold_uncertainty_score":0.01412565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01886500729238868,"score_gpt":0.2179875918905235,"score_spread":0.1991225845981348,"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."}}