{"id":"W4242752791","doi":"10.1515/iupac.78.0410","title":"Medium","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001162098,0.001804913,0.001336482,0.006749054,0.001013201,0.003445179,0.00253603,0.001898081,0.1843886],"category_scores_gemma":[0.01021634,0.0007120941,0.001310097,0.01269531,0.000449387,0.003830531,0.002573203,0.001966479,0.2068573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00226443,"about_ca_system_score_gemma":0.003409171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02662214,"about_ca_topic_score_gemma":0.04957286,"domain_scores_codex":[0.9982331,0.0002617417,0.000372987,0.0005459007,0.0003665514,0.0002197995],"domain_scores_gemma":[0.9958225,0.001214042,0.0005514182,0.0008328818,0.001257004,0.0003221219],"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":[0.00003785414,0.0000100041,0.000497812,0.0008140869,0.00001715158,0.00001612555,0.00002862535,0.00009250807,0.0001016096,0.0007540046,0.9948322,0.002798033],"study_design_scores_gemma":[0.00005618928,0.000006702729,0.001684575,0.0003918855,0.00001214757,0.00003585108,0.00007286886,0.00008870021,0.0001061511,0.0009207912,0.9966056,0.00001850012],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004313921,0.00005413868,0.00004678307,0.0000544493,0.00001675394,0.000009680553,0.998894,0.0001082588,0.0007728223],"genre_scores_gemma":[0.0001539835,0.00007083108,0.0001943518,0.00006099236,0.000005737392,0.00006554322,0.9986777,0.00004810998,0.0007227575],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8156114,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642894634231688,"score_gpt":0.4210720052645676,"score_spread":0.4046430589222507,"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."}}