{"id":"W2894690940","doi":"10.1016/j.smim.2018.09.003","title":"The integration of inflammaging in age-related diseases","year":2018,"lang":"en","type":"review","venue":"Seminars in Immunology","topic":"Immune responses and vaccinations","field":"Immunology and Microbiology","cited_by":347,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Institutes of Health Research; Agency for Science, Technology and Research","keywords":"Conceptualization; Context (archaeology); Adaptation (eye); Subclinical infection; Expansive; Medicine; Risk analysis (engineering); Psychology; Computer science; Biology; Neuroscience; Pathology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007976555,0.0008976635,0.001425191,0.001630345,0.0002639171,0.00138758,0.001020733,0.001593525,0.003068589],"category_scores_gemma":[0.0009181643,0.0002386377,0.0004001199,0.001486945,0.0007651075,0.001996287,0.001079055,0.00237015,0.001677509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004839651,"about_ca_system_score_gemma":0.00100521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004480014,"about_ca_topic_score_gemma":0.0008610008,"domain_scores_codex":[0.9997953,0.00003624742,0.0000330777,0.00003527724,0.00007363441,0.00002643318],"domain_scores_gemma":[0.9995553,0.0002229394,0.00006511068,0.00001386921,0.0000909523,0.00005192482],"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":[0.0001122155,0.00006425972,0.0001965436,0.01348119,0.00007730487,0.0003277675,0.00006985592,0.0002460282,0.001539098,0.005276128,0.04398734,0.9346223],"study_design_scores_gemma":[0.00002037216,0.00008039009,0.0009106747,0.003932372,0.00009065695,0.001664725,0.0000732317,0.00008228613,0.0002898683,0.003667953,0.9891671,0.00002028542],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005103598,0.9985189,0.00009985272,0.0003125832,0.0005883002,0.00000202333,0.000007900337,0.000004094145,0.0004154023],"genre_scores_gemma":[0.0005943627,0.9973463,0.0001341533,0.0002770181,0.001214754,0.000003802836,0.00001923182,0.000001088216,0.0004092497],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003068589,"threshold_uncertainty_score":0.01026547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01938375919177545,"score_gpt":0.3125881771052665,"score_spread":0.2932044179134911,"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."}}