{"id":"W4365147363","doi":"10.1515/iupac.94.0765","title":"Pseudo-Catalysis","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Catalysis and Oxidation Reactions","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Meaning (existential); Abandonment (legal); Field (mathematics); Computer science; Epistemology; Management science; Linguistics; Engineering; Philosophy; Political science; Mathematics","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":[0.001211836,0.003984366,0.001698481,0.003272783,0.001533397,0.003886125,0.004158591,0.002817955,0.09016539],"category_scores_gemma":[0.005798295,0.0008088755,0.003014944,0.004261042,0.0006091554,0.002552516,0.00308086,0.003280589,0.1770834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001843055,"about_ca_system_score_gemma":0.00281427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0197961,"about_ca_topic_score_gemma":0.04262463,"domain_scores_codex":[0.9984064,0.0003141686,0.0001697595,0.0005389339,0.0003375341,0.0002332878],"domain_scores_gemma":[0.9976671,0.000593585,0.0001761461,0.0009214103,0.0004249469,0.0002168741],"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":[0.0001366341,0.00004375781,0.0008423984,0.0009911032,0.00004748076,0.0000324312,0.00002579872,0.0004448886,0.0002567861,0.001334306,0.9913346,0.004509832],"study_design_scores_gemma":[0.0002127126,0.00003243271,0.002543092,0.0004586681,0.00003922438,0.0001106782,0.00007090523,0.0007533477,0.0006179033,0.003364572,0.991755,0.00004146672],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002685684,0.0003247017,0.0002238975,0.00008790384,0.00007104156,0.00002434114,0.9960175,0.0009459578,0.002036063],"genre_scores_gemma":[0.0003617734,0.0001110383,0.0004015922,0.00007360228,0.000008060131,0.00006455645,0.9981476,0.0000883048,0.0007435248],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09016539,"threshold_uncertainty_score":0.3016333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01483786769106442,"score_gpt":0.3747224166515608,"score_spread":0.3598845489604963,"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."}}