{"id":"W4241508944","doi":"10.1515/iupac.87.0607","title":"Sludde","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Management science; Chemistry; Linguistics; Engineering; Philosophy; Data mining; Organic chemistry","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":[0.001606799,0.001598986,0.001648289,0.004406715,0.000998653,0.004476601,0.002715535,0.00199867,0.1651217],"category_scores_gemma":[0.01223278,0.00076294,0.001676282,0.006781448,0.0004983057,0.002716966,0.003129199,0.001949425,0.2280627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001601269,"about_ca_system_score_gemma":0.003440133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01446735,"about_ca_topic_score_gemma":0.02877873,"domain_scores_codex":[0.9981865,0.0003541214,0.0003675841,0.0005434453,0.0003388814,0.0002094012],"domain_scores_gemma":[0.9959877,0.001144492,0.0004824282,0.001017039,0.001033905,0.000334375],"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":[0.00009839224,0.00001147122,0.0008556859,0.001161352,0.00002848523,0.00001771852,0.00002919969,0.0001351149,0.00006713039,0.0009400762,0.9925365,0.004118762],"study_design_scores_gemma":[0.000187187,0.00001602211,0.001556322,0.0006355242,0.00002143092,0.00004673735,0.00006151804,0.0001843904,0.000142716,0.001490825,0.9956374,0.0000200183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006399208,0.00007803116,0.00007029362,0.00009210739,0.00002950315,0.00001520197,0.9981711,0.0003717927,0.001107991],"genre_scores_gemma":[0.0002549151,0.0001072583,0.000287394,0.0001050843,0.00001143598,0.00008858678,0.997867,0.0001252164,0.001153131],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1651217,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01721605983890093,"score_gpt":0.4270438494669313,"score_spread":0.4098277896280303,"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."}}