{"id":"W4402514344","doi":"10.52843/cassyni.1spck4","title":"Advances in cpn60 barcoding for microbial species identification","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Identification (biology); DNA barcoding; Biology; Computational biology; Evolutionary biology; Ecology","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":[0.007202577,0.001907521,0.001637253,0.00633202,0.001057962,0.004486367,0.002886683,0.003156358,0.00666655],"category_scores_gemma":[0.01510484,0.001359298,0.001405969,0.005112805,0.002173626,0.00443363,0.005399907,0.004632105,0.01035291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001519868,"about_ca_system_score_gemma":0.002251559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002347883,"about_ca_topic_score_gemma":0.002159993,"domain_scores_codex":[0.9927493,0.001172433,0.0004240161,0.002653014,0.002663147,0.0003380338],"domain_scores_gemma":[0.9900475,0.004066168,0.0009732631,0.001865045,0.002619941,0.0004280785],"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":[0.0003238404,0.000100323,0.002722573,0.00475591,0.0001520306,0.000299606,0.0006679438,0.001616924,0.2158469,0.01943702,0.02053747,0.7335394],"study_design_scores_gemma":[0.00002815454,0.0002177573,0.005964428,0.001930268,0.0001358261,0.001628924,0.0003327788,0.008691419,0.3102791,0.02833272,0.6421633,0.0002952557],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02647213,0.06930692,0.8400459,0.005193304,0.002864727,0.0004566171,0.01360269,0.0120701,0.02998758],"genre_scores_gemma":[0.0573042,0.0510973,0.8399672,0.003777399,0.001624265,0.0007335012,0.02932961,0.003304342,0.01286221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007202577,"threshold_uncertainty_score":0.03809136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03726977659329336,"score_gpt":0.3271106780967435,"score_spread":0.2898409015034502,"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."}}