{"id":"W4293066864","doi":"10.1093/nar/gkac689","title":"Metagenomics versus total RNA sequencing: most accurate data-processing tools, microbial identification accuracy and perspectives for ecological assessments","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canada First Research Excellence Fund; University of Guelph","keywords":"Biology; Metagenomics; Identification (biology); Computational biology; Microbial ecology; Ecology; DNA sequencing; Data science; Genetics; Bacteria; Gene; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.03118249,0.002292059,0.002498153,0.003276295,0.0008546615,0.006769934,0.001795794,0.002386197,0.001314524],"category_scores_gemma":[0.02718855,0.0008159939,0.001471431,0.002795686,0.001874711,0.007188824,0.002156038,0.003302451,0.0008382541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001393134,"about_ca_system_score_gemma":0.001745721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001151358,"about_ca_topic_score_gemma":0.002385551,"domain_scores_codex":[0.9811539,0.00895162,0.001167884,0.003108779,0.004820166,0.0007976354],"domain_scores_gemma":[0.9780738,0.01069945,0.002888074,0.002824265,0.004893538,0.0006209693],"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":[0.00154845,0.0003358359,0.05311315,0.003985595,0.0007073342,0.000291368,0.001058339,0.00912749,0.5732996,0.01538617,0.00253055,0.338616],"study_design_scores_gemma":[0.00008861663,0.001120889,0.05959931,0.002454214,0.001173666,0.000973753,0.002251935,0.08477281,0.7288198,0.05716773,0.06102972,0.0005475346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1927817,0.05711727,0.7326842,0.008494576,0.0008170291,0.0003093571,0.002607764,0.001328732,0.003859413],"genre_scores_gemma":[0.3258375,0.01550218,0.651041,0.001991238,0.0004799154,0.0003184717,0.002546895,0.000835931,0.001446873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03118249,"threshold_uncertainty_score":0.1649107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2591727983652958,"score_gpt":0.4171740669071816,"score_spread":0.1580012685418858,"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."}}