{"id":"W4407735373","doi":"10.1007/s43657-024-00201-w","title":"Embracing Interpersonal Variability of Microbiome in Precision Medicine","year":2025,"lang":"en","type":"article","venue":"Phenomics","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Infection and Immunity","funders":"National Institute of Allergy and Infectious Diseases; National Institute on Aging; National Institutes of Health; Leona M. and Harry B. Helmsley Charitable Trust; Howard Hughes Medical Institute","keywords":"Microbiome; Precision medicine; Interpersonal communication; Computational biology; Biology; Medicine; Psychology; Bioinformatics; Genetics; Communication","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02210874,0.0003714763,0.001131983,0.001370099,0.001358225,0.005408903,0.0009211241,0.001566472,0.001920312],"category_scores_gemma":[0.0658209,0.0003155112,0.0005564528,0.0008860564,0.004535386,0.004283568,0.006279798,0.00371963,0.0002983971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001145352,"about_ca_system_score_gemma":0.002001947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121267,"about_ca_topic_score_gemma":0.001696795,"domain_scores_codex":[0.9803474,0.01462458,0.0004538164,0.00153938,0.002639938,0.0003949417],"domain_scores_gemma":[0.9280161,0.05403576,0.005302378,0.007790233,0.00329346,0.001562032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004551297,0.0003181153,0.2804019,0.001272189,0.002079711,0.001773259,0.01853783,0.008175734,0.01674565,0.1527432,0.01028911,0.5072082],"study_design_scores_gemma":[0.00007511524,0.0007589771,0.154309,0.001214357,0.0006743888,0.003271946,0.0124074,0.01183382,0.007873613,0.7293152,0.07800842,0.00025782],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3272177,0.03551394,0.4430285,0.1205655,0.004944525,0.0002498654,0.0009153528,0.0005878609,0.06697665],"genre_scores_gemma":[0.9389799,0.004510558,0.04440897,0.008142181,0.002744535,0.0001337435,0.00007739246,0.00009015924,0.0009124816],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02210874,"threshold_uncertainty_score":0.1169236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007243044838249161,"score_gpt":0.2846102880381159,"score_spread":0.2773672431998667,"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."}}