{"id":"W4283395221","doi":"10.1101/2022.02.21.480893","title":"Integrating phylogenetic and functional data in microbiome studies","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Tel Aviv University","keywords":"Metagenomics; Microbiome; Computational biology; Biology; Phylogenetic tree; Abundance (ecology); Evolutionary biology; Data science; Computer science; Ecology; Bioinformatics; Gene; Genetics","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":[0.01350181,0.001054515,0.001366473,0.009624313,0.0008513806,0.00277442,0.001211948,0.001381834,0.002815278],"category_scores_gemma":[0.03668839,0.0007422687,0.001290164,0.009346349,0.001452467,0.002782478,0.004733246,0.002313874,0.001045386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000770385,"about_ca_system_score_gemma":0.001157302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001773169,"about_ca_topic_score_gemma":0.002008243,"domain_scores_codex":[0.9932699,0.00454857,0.0002637809,0.0008777792,0.0008423321,0.0001976219],"domain_scores_gemma":[0.9769723,0.01506212,0.002164171,0.00312859,0.001676772,0.0009960176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001526351,0.0005541652,0.3784164,0.005362795,0.004076824,0.001285747,0.001397661,0.1425916,0.08880091,0.06023557,0.01346624,0.3022858],"study_design_scores_gemma":[0.0001119208,0.0003520599,0.1813509,0.001130124,0.0006579419,0.0008800688,0.001349572,0.329874,0.01888899,0.412056,0.05308173,0.0002667182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3427561,0.0123311,0.6025693,0.004280254,0.0004946001,0.0001917812,0.0254043,0.003270816,0.008701684],"genre_scores_gemma":[0.6467984,0.002700098,0.3356643,0.000819361,0.0003343415,0.0002072788,0.01245251,0.000572241,0.0004514788],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01350181,"threshold_uncertainty_score":0.07140523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03414636981978719,"score_gpt":0.2751053887399181,"score_spread":0.2409590189201309,"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."}}