{"id":"W2811490526","doi":"10.1016/j.biochi.2018.06.023","title":"Integration of the human exposome with the human genome to advance medicine","year":2018,"lang":"en","type":"review","venue":"Biochimie","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University and Génome Québec Innovation Centre","funders":"Université Paris Diderot; Seventh Framework Programme; Horizon 2020 Framework Programme; Université Paris Descartes; Institut National de la Santé et de la Recherche Médicale","keywords":"Exposome; Precision medicine; Systems medicine; Personalized medicine; Epigenome; Disease; Data science; Computational biology; Systems biology; Biology; Medicine; Bioinformatics; Computer science; Genetics; Pathology; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000733274,0.0003716709,0.0006276073,0.00005673808,0.0004441538,0.00001285616,0.0009369572,0.0001149319,0.0008265134],"category_scores_gemma":[0.00006353723,0.0001682203,0.0001242874,0.0004337734,0.0009627566,0.00007710212,0.0003857999,0.000360666,0.0003620551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003798812,"about_ca_system_score_gemma":0.00002744565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001572503,"about_ca_topic_score_gemma":0.0003469121,"domain_scores_codex":[0.9976276,0.0003251985,0.0005054357,0.0006486949,0.000556015,0.0003370755],"domain_scores_gemma":[0.9981762,0.0000892411,0.0005271003,0.001080052,0.0000104069,0.0001170015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000144392,0.000310698,0.0003575943,0.003934288,0.0002162525,0.00001173074,0.005315702,0.00002922955,0.02887932,0.001120327,0.007585221,0.9522252],"study_design_scores_gemma":[0.0001220315,0.0002592211,0.005673222,0.003336423,0.0001778536,0.000008454815,0.00009149898,4.507428e-7,0.000146027,0.00007034392,0.9898509,0.0002636211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01991506,0.9448718,0.001031543,0.001930772,0.0003364518,0.006875158,0.00009155799,0.00006963215,0.02487805],"genre_scores_gemma":[0.01785592,0.973811,0.000613041,0.002275295,0.0008234602,0.0005107342,0.0001011089,0.0001658179,0.003843592],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9822657,"threshold_uncertainty_score":0.9049742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04810730034368925,"score_gpt":0.3343185769511068,"score_spread":0.2862112766074176,"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."}}