{"id":"W4256379566","doi":"10.1515/iupac.88.1302","title":"Runt","year":2017,"lang":"sv","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; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001741206,0.001590012,0.001419104,0.00432928,0.001130066,0.004255949,0.00269978,0.001921181,0.1992235],"category_scores_gemma":[0.01387715,0.0007552562,0.001863659,0.007059803,0.0004879732,0.003005206,0.003211404,0.00199326,0.264942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001673208,"about_ca_system_score_gemma":0.003121373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01640615,"about_ca_topic_score_gemma":0.03216453,"domain_scores_codex":[0.9977396,0.0004509509,0.0004519055,0.000664723,0.0004434253,0.0002495613],"domain_scores_gemma":[0.9946483,0.001581892,0.0006476099,0.00142488,0.001355551,0.0003418518],"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":[0.00007720114,0.00001051931,0.0007215165,0.00107152,0.00002595132,0.00001372783,0.0000305138,0.0001084005,0.00006146899,0.0008648134,0.9927176,0.004296688],"study_design_scores_gemma":[0.0001352098,0.0000150839,0.001999232,0.0006275683,0.0000210407,0.00004499989,0.00007212645,0.0001444606,0.0001364153,0.001419184,0.9953614,0.00002330526],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007187182,0.00007866521,0.00008254767,0.00009143924,0.00003503117,0.00001949079,0.9976694,0.0003913874,0.001560122],"genre_scores_gemma":[0.0002539596,0.00009130452,0.000299094,0.0001112495,0.00001312119,0.0001025685,0.9977047,0.0001551341,0.001268825],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8007765,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0239520397614122,"score_gpt":0.4637459962089313,"score_spread":0.4397939564475191,"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."}}