{"id":"W3117245766","doi":"10.20900/immunometab20210002","title":"Gearing up for the Future: Mitigating Dysregulated Inflammation in Aging and Facets of Obesity","year":2020,"lang":"en","type":"article","venue":"Immunometabolism","topic":"Adipokines, Inflammation, and Metabolic Diseases","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Obesity; Overweight; Metabolic syndrome; Inflammation; Medicine; Psychological intervention; Population ageing; Population; Immune system; Systemic inflammation; Gerontology; Immunology; Environmental health; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002811155,0.0001313732,0.000332868,0.00009007933,0.00009809862,0.000025832,0.00009033681,0.00005485496,0.00001830626],"category_scores_gemma":[0.0002889702,0.0001004439,0.00007836968,0.0002979957,0.00007555549,0.0001959762,0.00004443452,0.0001129479,0.000001804181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001002316,"about_ca_system_score_gemma":0.00006318285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005166194,"about_ca_topic_score_gemma":0.000007432891,"domain_scores_codex":[0.9990373,0.00003599357,0.0004120703,0.0001738546,0.0001605462,0.000180264],"domain_scores_gemma":[0.9993526,0.0001036466,0.0001731447,0.0001743686,0.0001201236,0.00007612767],"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":[0.0006616061,0.0001059285,0.09755907,0.001736519,0.0005215605,0.000006317056,0.02998506,0.0006699298,0.3203692,0.01385326,0.0001632201,0.5343683],"study_design_scores_gemma":[0.002654036,0.00002492403,0.957789,0.0001004577,0.0002442707,0.000005788564,0.001526267,0.003899467,0.01563001,0.0002248746,0.01776935,0.0001315756],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785711,0.0174438,0.0006050321,0.002289989,0.0002669141,0.0006748395,0.00001343529,0.00003957601,0.00009536856],"genre_scores_gemma":[0.9976514,0.0007216731,0.0005976616,0.000183067,0.0006973713,0.00003590593,0.00003342382,0.00001767592,0.0000617994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8602299,"threshold_uncertainty_score":0.4095981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01460206435017593,"score_gpt":0.2530162544306233,"score_spread":0.2384141900804474,"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."}}