{"id":"W2982504733","doi":"10.1186/s40168-019-0755-x","title":"Microbiota analysis optimization for human bronchoalveolar lavage fluid","year":2019,"lang":"en","type":"article","venue":"Microbiome","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; University Health Network","keywords":"Bronchoalveolar lavage; Biology; 16S ribosomal RNA; Computational biology; Genetics; Gene; Lung; Medicine; Internal medicine","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":[0.0002040604,0.0002207078,0.0002940683,0.0002211305,0.0001543042,0.00005358808,0.0002701558,0.0002510227,0.0003657357],"category_scores_gemma":[0.000007768471,0.0002291819,0.0003170273,0.0002951547,0.00005200346,0.000005976033,0.00009880521,0.00007037286,0.00009300428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004154115,"about_ca_system_score_gemma":0.00006015623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004621211,"about_ca_topic_score_gemma":0.00006396328,"domain_scores_codex":[0.9986148,0.00004178321,0.000306619,0.0005736343,0.0000466155,0.0004165552],"domain_scores_gemma":[0.999111,0.000007076108,0.0001183124,0.0005618766,0.0001182882,0.00008343018],"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":[0.00003650716,0.0000693432,0.001815888,0.00006799079,0.0002998104,3.3275e-7,0.00003803107,0.001097416,0.9895816,0.00002924156,0.006894999,0.00006883454],"study_design_scores_gemma":[0.002282161,0.0005229852,0.005396172,0.00002251493,0.0004210177,0.00001508628,0.00005076732,0.0004143227,0.7644342,0.000009984406,0.2257226,0.0007082247],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821537,0.0005354023,0.0155714,0.0001432605,0.0002037341,0.0006865616,0.0003118431,0.00003069269,0.0003634484],"genre_scores_gemma":[0.9778416,0.00005354027,0.008464478,0.0007472932,0.0001654327,0.00002019415,0.005319331,0.00005258426,0.007335585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2251474,"threshold_uncertainty_score":0.9345766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005469925355109173,"score_gpt":0.2562560856112259,"score_spread":0.2507861602561167,"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."}}