{"id":"W4252011285","doi":"10.1515/iupac.78.0571","title":"SOP","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Management science; Data science; Chemistry; Engineering; Data mining; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001099596,0.001833604,0.001301085,0.006237824,0.001034433,0.003039161,0.0026239,0.00173584,0.1728854],"category_scores_gemma":[0.00876321,0.0006029822,0.001278279,0.01236473,0.0004235404,0.002820547,0.002625339,0.001794449,0.200116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002095858,"about_ca_system_score_gemma":0.003504098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02833077,"about_ca_topic_score_gemma":0.05031941,"domain_scores_codex":[0.998387,0.000257744,0.0003223601,0.0004882566,0.0003551274,0.0001894161],"domain_scores_gemma":[0.9965314,0.0009328983,0.0004736878,0.0006875701,0.001112025,0.0002624223],"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":[0.00003414609,0.000009035526,0.0005230367,0.000829836,0.00001547672,0.00001584425,0.00002793908,0.0001044665,0.00007980721,0.0008243092,0.9946426,0.002893403],"study_design_scores_gemma":[0.00005291842,0.000006934611,0.001672178,0.0004480457,0.00001226145,0.0000345675,0.00006987497,0.00009600033,0.00009753211,0.00103858,0.9964557,0.00001553178],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003556901,0.00004432812,0.00003996284,0.00004772032,0.0000111221,0.000007611048,0.9990317,0.0001000441,0.0006819518],"genre_scores_gemma":[0.0001390239,0.00006950953,0.0001759189,0.00005446793,0.000004803027,0.00006132059,0.9987643,0.00004919637,0.0006814081],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8271146,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764981819806675,"score_gpt":0.431340465944681,"score_spread":0.4136906477466142,"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."}}