{"id":"W4403655095","doi":"10.1038/s41598-024-75110-z","title":"Computational algorithm based on health and lifestyle traits to categorize lifemetabotypes in the NUTRiMDEA cohort","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Categorization; Cohort; Computer science; Cohort study; Algorithm; Medicine; Artificial intelligence; Internal medicine","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":[0.00570687,0.0005795156,0.0006641482,0.002294468,0.0007674833,0.00123123,0.0009895986,0.0005929965,0.003354862],"category_scores_gemma":[0.0203681,0.0002785619,0.001167709,0.001146754,0.0003861836,0.0005087752,0.001124731,0.0008269315,0.0007841139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008306539,"about_ca_system_score_gemma":0.001976076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00826175,"about_ca_topic_score_gemma":0.00903165,"domain_scores_codex":[0.9983612,0.0008344033,0.0001619687,0.0003664104,0.0001789656,0.00009698619],"domain_scores_gemma":[0.9935097,0.004629056,0.0004320023,0.000561459,0.0007188776,0.00014881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00215589,0.00120199,0.4317133,0.0003265899,0.0009497812,0.0002270494,0.001475659,0.08497788,0.003876388,0.008659612,0.01529838,0.4491375],"study_design_scores_gemma":[0.0002785322,0.0002753192,0.05259028,0.00008452198,0.000160562,0.00016392,0.0007158831,0.9273989,0.002314675,0.01119094,0.00476845,0.00005794896],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4931656,0.000252769,0.4924552,0.001652506,0.0001695626,0.001766869,0.004137075,0.002550728,0.003849604],"genre_scores_gemma":[0.4922386,0.00007786225,0.4987459,0.0003392616,0.00004573782,0.0021414,0.004425045,0.0001389095,0.001847316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00826175,"threshold_uncertainty_score":0.03018123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008179073534113403,"score_gpt":0.2656166865677201,"score_spread":0.2574376130336067,"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."}}