{"id":"W4407356111","doi":"10.1186/s40168-024-02015-4","title":"PhyloFunc: phylogeny-informed functional distance as a new ecological metric for metaproteomic data analysis","year":2025,"lang":"en","type":"article","venue":"Microbiome","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Biology; Microbial ecology; Ecology; Metric (unit); Phylogenetics; Evolutionary biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002791261,0.0002309715,0.0003628476,0.0003692267,0.0001833117,0.00005668474,0.0005915961,0.0002390747,0.00019209],"category_scores_gemma":[0.0002597265,0.0002061888,0.0002703445,0.001235456,0.00008001959,0.000008231873,0.0003495164,0.00009786984,0.00005188132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009216215,"about_ca_system_score_gemma":0.001075296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000814893,"about_ca_topic_score_gemma":0.0003757255,"domain_scores_codex":[0.9983332,0.00003737707,0.0003657608,0.0007610825,0.00006909015,0.0004334515],"domain_scores_gemma":[0.998687,0.00004502856,0.0001245483,0.0009059457,0.00009635698,0.0001411764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002179193,0.0001078175,0.0006666065,0.00005307675,0.0009252235,7.608459e-7,0.000006603956,0.00002539343,0.8561583,0.0002745897,0.1402035,0.001360251],"study_design_scores_gemma":[0.001827328,0.0002399874,0.01784591,0.000008484186,0.0008428441,0.000009814798,0.00002762243,0.0001208223,0.08678047,0.0002532779,0.8916718,0.0003716488],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5755179,0.006571006,0.4057818,0.003463104,0.001097281,0.002229122,0.003039291,0.00008926701,0.002211181],"genre_scores_gemma":[0.9400389,0.0002137408,0.01478301,0.004616141,0.0003263815,0.00007777764,0.01185415,0.00002703554,0.02806288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7693778,"threshold_uncertainty_score":0.8408137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02954114101264183,"score_gpt":0.3233870817683732,"score_spread":0.2938459407557313,"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."}}