{"id":"W4231322253","doi":"10.1515/iupac.79.1482","title":"Inflammation","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Inflammasome and immune disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; Computer science; Toxicology; Chemistry; Philosophy; Biology; 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":[0.001066423,0.001591492,0.001946544,0.002620299,0.0006229227,0.0025051,0.00166698,0.001592847,0.07909995],"category_scores_gemma":[0.008299687,0.0004137081,0.002345993,0.004587969,0.0002367664,0.001334045,0.001337134,0.001414253,0.05029225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001076145,"about_ca_system_score_gemma":0.002139152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007234842,"about_ca_topic_score_gemma":0.01633434,"domain_scores_codex":[0.9983897,0.0002964219,0.0003767579,0.0005019249,0.0002653232,0.0001698026],"domain_scores_gemma":[0.9977969,0.0007128093,0.000504941,0.0003893098,0.0004359161,0.0001601714],"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":[0.0009670538,0.00005484414,0.008797138,0.007463799,0.000356959,0.0001018672,0.00004922475,0.0004947265,0.000276878,0.000836271,0.9552711,0.02533019],"study_design_scores_gemma":[0.001014266,0.0001091664,0.02432238,0.003669539,0.0005486667,0.0006266033,0.0001127906,0.0004563192,0.0005036236,0.003312499,0.9652522,0.00007193154],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004268193,0.00137936,0.0001161874,0.0001482667,0.00007390713,0.00005136563,0.9955296,0.0001670389,0.002107445],"genre_scores_gemma":[0.001964126,0.001170771,0.0005117074,0.0003823193,0.00006039753,0.0003245749,0.9934747,0.00004509163,0.002066305],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07909995,"threshold_uncertainty_score":0.2646157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006118666016408353,"score_gpt":0.3462584793087577,"score_spread":0.3401398132923494,"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."}}