{"id":"W2905561504","doi":"10.1101/501940","title":"Drivers of human gut microbial community assembly: Coadaptation, determinism and stochasticity","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; McMaster University","keywords":"Firmicutes; Microbial population biology; Ecosystem; Biology; Microbial ecology; Bacterioplankton; Bacteroidetes; Ecology; Bacteria; Nutrient; Genetics; 16S ribosomal RNA","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":[0.000947825,0.0001748165,0.0002897675,0.0003537521,0.0002150706,0.0007822642,0.000191691,0.0003257403,0.0006576342],"category_scores_gemma":[0.001808793,0.000194091,0.0001862833,0.0002685635,0.000494735,0.0002682132,0.0005896416,0.0003303429,0.00009639373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003393694,"about_ca_system_score_gemma":0.0002762722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00105416,"about_ca_topic_score_gemma":0.001180941,"domain_scores_codex":[0.9992785,0.0002676182,0.00003441098,0.0002188511,0.0001233029,0.0000773785],"domain_scores_gemma":[0.9987483,0.0003636531,0.0004945213,0.0001675687,0.000108321,0.0001175153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000741686,0.0001134291,0.583004,0.0001674804,0.0002455521,0.0004869784,0.0005769009,0.005134806,0.3896864,0.00153719,0.0002193671,0.01808625],"study_design_scores_gemma":[0.00001751206,0.0003722991,0.9220315,0.00002550494,0.00007582839,0.0008788797,0.0009935249,0.01697988,0.05365554,0.003409472,0.001508011,0.00005203077],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955777,0.0002682318,0.003613731,0.0001129993,0.000004207995,0.000007695321,0.0001353786,0.0000140037,0.00026605],"genre_scores_gemma":[0.9992412,0.00004831244,0.0005944162,0.0000137562,0.000004050973,0.000004258635,0.00004395455,0.000002837284,0.00004716733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00105416,"threshold_uncertainty_score":0.005012572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01912288811990793,"score_gpt":0.2563737672672352,"score_spread":0.2372508791473272,"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."}}