{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01391906,0.002728133,0.002960555,0.004371716,0.00260773,0.002687571,0.002257231,0.002920953,0.008521208],"category_scores_gemma":[0.01590072,0.001601622,0.002478605,0.002603239,0.002493402,0.001547339,0.004041066,0.003974491,0.01577205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007032711,"about_ca_system_score_gemma":0.004402008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009759459,"about_ca_topic_score_gemma":0.00205824,"domain_scores_codex":[0.9835976,0.004245087,0.002416359,0.004102197,0.004528418,0.00111033],"domain_scores_gemma":[0.9860021,0.002441847,0.001199883,0.005361239,0.004493873,0.0005010679],"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":[0.000381099,0.0003075806,0.00311844,0.001355611,0.0001449452,0.0003801926,0.0006836914,0.0007523468,0.9423774,0.001534118,0.00340812,0.04555655],"study_design_scores_gemma":[0.0001580432,0.00206802,0.02400223,0.0009691307,0.0005211196,0.001784433,0.0005153955,0.005966176,0.8017328,0.004947188,0.1569332,0.0004022066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02334108,0.001592871,0.9505029,0.0003441428,0.0007889242,0.01205978,0.004021547,0.00399575,0.003353075],"genre_scores_gemma":[0.0350251,0.001757985,0.9167736,0.0007575299,0.0002833189,0.03023904,0.009762391,0.001339099,0.004062056],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01391906,"threshold_uncertainty_score":0.07361186,"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."}}