{"id":"W3199301331","doi":"","title":"From Molecular Profiling to Precision Medicine in Metabolic Syndrome","year":2019,"lang":"fr","type":"preprint","venue":"Prodinra (INRA Bordeaux-Aquitaine)","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Dyslipidemia; Context (archaeology); Metabolic syndrome; Medicine; Feature selection; Metabolomics; Computer science; Computational biology; Bioinformatics; Obesity; Internal medicine; Artificial intelligence; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01080651,0.001328105,0.002877709,0.003794838,0.0003873628,0.003819591,0.001445617,0.001613109,0.00175787],"category_scores_gemma":[0.0139302,0.0005259442,0.001417513,0.003118245,0.001851915,0.001755503,0.00262927,0.002780555,0.0009152409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00146254,"about_ca_system_score_gemma":0.001655774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001925094,"about_ca_topic_score_gemma":0.001875674,"domain_scores_codex":[0.9955713,0.002239553,0.0002428689,0.0008080928,0.0009706968,0.0001675211],"domain_scores_gemma":[0.9901103,0.006326895,0.0008041984,0.001193532,0.00128884,0.0002761521],"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":[0.001236028,0.0001913752,0.04060687,0.003922421,0.002645323,0.0005229096,0.0004009838,0.01339643,0.01458905,0.02820231,0.01836397,0.8759223],"study_design_scores_gemma":[0.0005384461,0.003171586,0.1178564,0.009465653,0.003479577,0.003750257,0.0008625197,0.1290407,0.03618811,0.4218276,0.2729887,0.000830483],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.04946979,0.5115899,0.3822564,0.03817992,0.002809504,0.0002671404,0.003689788,0.002315857,0.009421642],"genre_scores_gemma":[0.3914257,0.2765765,0.2998695,0.01959352,0.005850023,0.0004761526,0.002914874,0.0003633625,0.002930404],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01080651,"threshold_uncertainty_score":0.05715102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322483405759887,"score_gpt":0.279901287271145,"score_spread":0.2666764532135461,"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."}}