{"id":"W4235021271","doi":"10.1515/iupac.79.1547","title":"Limit Test","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 Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; Computer science; Toxicology; Chemistry; Philosophy; Biology; 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":[0.005078562,0.001992126,0.002266956,0.003902734,0.001123336,0.004277327,0.005345282,0.002489015,0.2123774],"category_scores_gemma":[0.04876449,0.0005790811,0.003489816,0.00374505,0.0006945888,0.003245976,0.002107692,0.002706786,0.1238858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002065658,"about_ca_system_score_gemma":0.004048748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01063818,"about_ca_topic_score_gemma":0.01521682,"domain_scores_codex":[0.9946116,0.001084324,0.00085488,0.001825422,0.00119378,0.0004300794],"domain_scores_gemma":[0.9814197,0.00945581,0.001346306,0.003555293,0.003715919,0.0005069711],"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":[0.0009368533,0.0001284527,0.009279042,0.002138218,0.0003848734,0.00008661531,0.00004586844,0.001776561,0.0001256043,0.00380678,0.9299418,0.05134928],"study_design_scores_gemma":[0.0009492954,0.0002254531,0.01103262,0.001739583,0.0004182636,0.0004078333,0.0002123267,0.004462716,0.0008241488,0.02032699,0.9592996,0.0001011033],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001695076,0.001004366,0.002404462,0.000613653,0.0003836513,0.0003038187,0.9801325,0.001601795,0.01186057],"genre_scores_gemma":[0.01084913,0.0006395755,0.00501692,0.001125728,0.0002156067,0.001220368,0.9683223,0.0006892344,0.01192115],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7876226,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01842994977756561,"score_gpt":0.4131798599851693,"score_spread":0.3947499102076036,"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."}}