{"id":"W4365142143","doi":"10.1515/iupac.94.0474","title":"Excess Acidity","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Various Chemistry Research Topics","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Meaning (existential); Abandonment (legal); Field (mathematics); Epistemology; Chemistry; Linguistics; Philosophy; Mathematics; Political science","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":[0.000668507,0.002379141,0.001527838,0.003453224,0.001226503,0.002775857,0.002410832,0.00176334,0.07885987],"category_scores_gemma":[0.003443634,0.0005669854,0.001562179,0.004493256,0.0004220013,0.002281434,0.002173396,0.002071538,0.1457945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001218844,"about_ca_system_score_gemma":0.001474306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01659539,"about_ca_topic_score_gemma":0.04253296,"domain_scores_codex":[0.9991493,0.0001189497,0.0001127508,0.0002846599,0.0002076177,0.0001266727],"domain_scores_gemma":[0.9987226,0.0002576964,0.00014326,0.0004124753,0.0003377423,0.0001261548],"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":[0.0001432314,0.0000318643,0.001237716,0.001085078,0.00002941693,0.00003071118,0.00003105827,0.0002487341,0.0004115543,0.0007196445,0.9903035,0.005727529],"study_design_scores_gemma":[0.0001499266,0.00002725369,0.006424886,0.0004245936,0.000031126,0.0001134803,0.0001006505,0.0004455034,0.0006803836,0.002065235,0.9894862,0.00005075157],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004080524,0.0002700238,0.0001104618,0.00006897604,0.00005915834,0.00001927934,0.9963157,0.0004785067,0.002269934],"genre_scores_gemma":[0.0004718719,0.000129243,0.0003502792,0.00006441874,0.00001028204,0.00004878965,0.9978999,0.00005740537,0.0009676717],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07885987,"threshold_uncertainty_score":0.2638125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03280245593318734,"score_gpt":0.4443831262178909,"score_spread":0.4115806702847036,"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."}}