{"id":"W4365147586","doi":"10.1515/iupac.94.0478","title":"Exsy","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; Computer science; Linguistics; 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":[0.001101482,0.002489597,0.00132612,0.003387089,0.001215266,0.002853959,0.002755322,0.001783623,0.1690421],"category_scores_gemma":[0.004925805,0.000643666,0.001485056,0.00445484,0.0005054494,0.002422013,0.003093223,0.002111096,0.3272682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001310674,"about_ca_system_score_gemma":0.001765475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01641569,"about_ca_topic_score_gemma":0.04122199,"domain_scores_codex":[0.9988319,0.0002491236,0.0001550907,0.0003551698,0.0002443916,0.0001641859],"domain_scores_gemma":[0.9982241,0.0004083795,0.000156846,0.0006115737,0.0004303394,0.0001688707],"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":[0.00004816608,0.00001633896,0.0003156691,0.0003703382,0.00001311163,0.0000143811,0.0000203312,0.00008717926,0.0001199733,0.0004211241,0.9955977,0.002975811],"study_design_scores_gemma":[0.00009473514,0.00001992763,0.00185812,0.0001980577,0.00001283486,0.00006064194,0.00007701898,0.0002240977,0.0002691595,0.00122121,0.9959397,0.00002435537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001302845,0.00009881544,0.0001168827,0.00008595926,0.00005062338,0.00001734443,0.997127,0.0006517731,0.001721328],"genre_scores_gemma":[0.0001579983,0.00005282262,0.0002308313,0.00007494204,0.000008399037,0.00004992858,0.9982029,0.00008597269,0.001136145],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1690421,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02638971837735352,"score_gpt":0.4374853578729387,"score_spread":0.4110956394955853,"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."}}