{"id":"W4246273435","doi":"10.1515/iupac.87.0172","title":"Cue","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; Relation (database); Chemical nomenclature; Computer science; Psychology; Chemistry; Linguistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00115608,0.0008958666,0.001113231,0.0005655218,0.0001478897,0.0001091794,0.001178913,0.0007452846,0.02851606],"category_scores_gemma":[0.001542818,0.0006647268,0.0003380273,0.0004245133,0.000336887,0.0001747258,0.000432203,0.0008966787,0.000514489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001546139,"about_ca_system_score_gemma":0.001949588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001716215,"about_ca_topic_score_gemma":0.002217918,"domain_scores_codex":[0.9944429,0.0002038002,0.0007507923,0.0009841972,0.002665708,0.0009526432],"domain_scores_gemma":[0.9955837,0.0001493806,0.0005393093,0.002347035,0.0009784573,0.0004021837],"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":[0.0002978701,0.00027347,0.000002810859,0.0001192635,0.0001992513,0.0002234479,0.000004535262,5.208336e-7,0.00003447555,0.00001067496,0.9961329,0.002700759],"study_design_scores_gemma":[0.001543739,0.0001895167,0.00001547791,0.0006646025,0.0002386044,0.00004565668,0.000007912391,0.000001218374,0.00003107905,0.0002095247,0.9961579,0.0008947102],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001706446,0.0009052517,0.0000427174,0.0003822384,0.001385437,0.0004538782,0.996277,0.0003576331,0.0001787724],"genre_scores_gemma":[0.000002803215,0.0005051366,0.00005429181,0.0002775324,0.002781942,0.00002491042,0.9947854,0.0002762024,0.001291737],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02800157,"threshold_uncertainty_score":0.9995804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01661653877941268,"score_gpt":0.4293854033452478,"score_spread":0.4127688645658352,"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."}}