{"id":"W4298125100","doi":"10.1093/bioinformatics/btac655","title":"Integrating phylogenetic and functional data in microbiome studies","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Tel Aviv University; Israel Science Foundation","keywords":"Phylogenetic tree; Microbiome; Computational biology; Metagenomics; Biology; Computer science; Evolutionary biology; Data science; Bioinformatics; Genetics; Gene","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":[0.01927925,0.001675976,0.001888695,0.009504028,0.001469867,0.004025702,0.002300594,0.001935312,0.005576645],"category_scores_gemma":[0.06910492,0.001406214,0.001977646,0.01186727,0.001831073,0.004411818,0.007831227,0.003329266,0.002997314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040024,"about_ca_system_score_gemma":0.002324911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002731382,"about_ca_topic_score_gemma":0.004186905,"domain_scores_codex":[0.9886394,0.00689366,0.0005464813,0.001972525,0.001634127,0.0003137975],"domain_scores_gemma":[0.9575362,0.02921601,0.003348243,0.004628386,0.003266912,0.002004228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002725987,0.0005794828,0.3019386,0.01080593,0.004765377,0.001379807,0.002530747,0.1010431,0.06880355,0.0552619,0.05239484,0.3977706],"study_design_scores_gemma":[0.000295781,0.0004748022,0.1368383,0.002417053,0.001298987,0.001870479,0.001183201,0.2842386,0.02879355,0.408593,0.1334444,0.0005518517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1316315,0.01248701,0.7632691,0.007089581,0.0006370254,0.0003654799,0.0614434,0.01524951,0.007827406],"genre_scores_gemma":[0.2804045,0.004259488,0.6757295,0.001918671,0.0005791318,0.0004869837,0.03259704,0.003118984,0.0009057685],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01927925,"threshold_uncertainty_score":0.1019596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04460253469201658,"score_gpt":0.2973678979865577,"score_spread":0.2527653632945411,"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."}}