{"id":"W4245453334","doi":"10.1515/iupac.78.0201","title":"Cation","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":[],"consensus_categories":[],"category_scores_codex":[0.001658296,0.001836508,0.001404831,0.00612857,0.001121998,0.003228342,0.003388646,0.00222463,0.1871365],"category_scores_gemma":[0.01232468,0.0006126766,0.001459877,0.009981388,0.0004997558,0.003991791,0.002363048,0.002129077,0.1888279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002354214,"about_ca_system_score_gemma":0.003915138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03134347,"about_ca_topic_score_gemma":0.05207714,"domain_scores_codex":[0.9973921,0.0003758952,0.0005105977,0.0008699311,0.0005871937,0.0002643376],"domain_scores_gemma":[0.9949227,0.001320156,0.0006867542,0.001196739,0.001568321,0.0003053645],"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":[0.00003672114,0.000009455787,0.0005965318,0.0005664528,0.00001496276,0.00001634934,0.00002276498,0.0001017826,0.0000644376,0.0008562698,0.9950697,0.002644534],"study_design_scores_gemma":[0.0000849015,0.000007396385,0.001884789,0.0004728679,0.00001468854,0.00005351117,0.00008631206,0.0001738476,0.0001214486,0.00137909,0.9956995,0.00002168965],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005487273,0.00005515336,0.00006640062,0.0000883988,0.00001724358,0.00001609153,0.9986966,0.0001521516,0.0008530173],"genre_scores_gemma":[0.0002081595,0.00006196056,0.0002586698,0.00009519934,0.000007285871,0.0001126529,0.9983659,0.00004951633,0.0008406959],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1871365,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663879593210525,"score_gpt":0.4326561393968699,"score_spread":0.4160173434647646,"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."}}