{"id":"W4232318145","doi":"10.1515/iupac.81.0799","title":"Saprobien Spectrum","year":2016,"lang":"de","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Computer science; Ecology; Biology; Data mining; Linguistics; Philosophy","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":[0.001352887,0.00277407,0.001753645,0.00447141,0.001228946,0.003824678,0.003530741,0.002230608,0.08126424],"category_scores_gemma":[0.00640036,0.0007148485,0.001595658,0.006109621,0.0005846936,0.002732451,0.002865707,0.002663282,0.1885176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001747189,"about_ca_system_score_gemma":0.002607097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01476771,"about_ca_topic_score_gemma":0.02949595,"domain_scores_codex":[0.9984065,0.0002546902,0.0001799411,0.0005908407,0.0003530676,0.0002151096],"domain_scores_gemma":[0.9980549,0.000426779,0.000203411,0.0005516427,0.0005143438,0.0002489277],"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":[0.00009738501,0.0000223826,0.0008058294,0.0007582946,0.00002903144,0.00002744189,0.00002740954,0.0002572503,0.0001333835,0.0008659781,0.9929612,0.004014283],"study_design_scores_gemma":[0.0001620917,0.00001947241,0.002260767,0.0003285919,0.00001991773,0.00008101753,0.00007896984,0.0005608124,0.0003254815,0.001986976,0.9941502,0.00002574981],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001731456,0.0001760318,0.0001209948,0.0001065882,0.00003725096,0.00001744624,0.9972385,0.0008183278,0.001311616],"genre_scores_gemma":[0.000345806,0.0001123083,0.0003569531,0.00006796696,0.000008145445,0.00006012163,0.9982298,0.000100714,0.000718068],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08126424,"threshold_uncertainty_score":0.271856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011586081522862,"score_gpt":0.3736090531004443,"score_spread":0.3620229715775823,"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."}}