{"id":"W4241220132","doi":"10.1515/iupac.84.0688","title":"Immune Equilibrium","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Immunotoxicology; Immunology; Medicine; Immune system; Philosophy; Linguistics","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":[0.001332004,0.001557454,0.001372113,0.003247422,0.0007782396,0.003321473,0.003051926,0.002075103,0.08247471],"category_scores_gemma":[0.01331773,0.0005708685,0.001999378,0.004792009,0.0003398636,0.002030503,0.002020938,0.002376592,0.07846793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001929308,"about_ca_system_score_gemma":0.002695748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0175373,"about_ca_topic_score_gemma":0.02774907,"domain_scores_codex":[0.9984211,0.0002720325,0.000275583,0.0005056398,0.0003220518,0.0002035998],"domain_scores_gemma":[0.9964185,0.001091613,0.0004906671,0.0008191629,0.0009059008,0.000274108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001953808,0.0000374252,0.005167343,0.001507647,0.0001074577,0.00003484934,0.00003096397,0.0006695918,0.00006654047,0.002493138,0.9787284,0.01096125],"study_design_scores_gemma":[0.0002762471,0.00002566486,0.006532072,0.0007737452,0.00006033955,0.0001356958,0.00006707659,0.0006894579,0.0001753769,0.003990628,0.9872466,0.00002704531],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002927786,0.0002681023,0.0001970668,0.0001674025,0.00005533849,0.0000256216,0.9965671,0.0002873433,0.002139191],"genre_scores_gemma":[0.001541344,0.0002610259,0.0006471294,0.0002733859,0.00003011112,0.0001596263,0.9951937,0.00007950083,0.001814148],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08247471,"threshold_uncertainty_score":0.2759054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02336471323669108,"score_gpt":0.4132694101732809,"score_spread":0.3899046969365898,"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."}}