{"id":"W3126184699","doi":"10.1038/s42003-021-01690-5","title":"Development of a robust protocol for the characterization of the pulmonary microbiota","year":2021,"lang":"en","type":"article","venue":"Communications Biology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Fonds de Recherche du Québec - Santé; Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Fondation Institut Universitaire de Cardiologie et de Pneumologie de Québec","keywords":"Standardization; Amplicon sequencing; Workflow; Computational biology; Amplicon; DNA extraction; Biology; Microbiome; Protocol (science); Lung; Homogenization (climate); 16S ribosomal RNA; Computer science; Bioinformatics; Polymerase chain reaction; Medicine; Pathology; Gene; Genetics; Internal medicine; Ecology; Biodiversity","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001527604,0.00005706283,0.00008590684,0.0000115693,0.0001904269,0.000002738334,0.0005714819,0.00008766352,0.000008198811],"category_scores_gemma":[0.00004387522,0.00003598158,0.0000559504,0.00009161736,0.0001868476,0.000001023146,0.0004374095,0.00005276617,6.283871e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007576401,"about_ca_system_score_gemma":0.0003267739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002790206,"about_ca_topic_score_gemma":0.00006180076,"domain_scores_codex":[0.9994282,0.0001086287,0.0002560015,0.0001041975,0.00001532096,0.00008761932],"domain_scores_gemma":[0.9985546,0.00003269547,0.0001767731,0.001038316,0.0001873138,0.00001033485],"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":[0.00001736115,0.00009724002,0.001172312,0.00003941821,0.00002390848,4.962967e-9,0.000070889,9.611495e-7,0.9954448,0.0005694772,0.00008468141,0.002478969],"study_design_scores_gemma":[0.0002157095,0.0000226639,0.02802498,0.00002227961,0.000008069682,0.000005787956,0.00005515253,0.00003881267,0.5442029,0.00002016812,0.4273362,0.0000473094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7692009,0.00155369,0.03530157,0.01963562,0.0004942451,0.1710076,0.000787147,0.00002972242,0.001989475],"genre_scores_gemma":[0.885682,0.0002275613,0.0429374,0.0007367778,0.00007672144,0.06771153,0.001803677,0.00002826823,0.0007960441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4512419,"threshold_uncertainty_score":0.1467286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06657601610666412,"score_gpt":0.3435599544151946,"score_spread":0.2769839383085305,"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."}}