{"id":"W4251270988","doi":"10.1515/iupac.79.1490","title":"Intake","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; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001826638,0.001700302,0.001756809,0.004163031,0.000999447,0.003800006,0.002805731,0.001939626,0.2936281],"category_scores_gemma":[0.01712511,0.0007060011,0.00164241,0.008171674,0.0003527068,0.002935757,0.002398612,0.001838378,0.2913511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002302116,"about_ca_system_score_gemma":0.003668643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02117025,"about_ca_topic_score_gemma":0.03549928,"domain_scores_codex":[0.9975029,0.0004109912,0.0004658731,0.0008435052,0.0005062983,0.0002703878],"domain_scores_gemma":[0.9925547,0.00195701,0.0007530601,0.001485136,0.002815673,0.000434315],"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":[0.0000680138,0.00001210653,0.0008643076,0.0007016767,0.00002555345,0.00001052574,0.00001529309,0.00007942122,0.00003432699,0.0004474505,0.9933091,0.004432273],"study_design_scores_gemma":[0.0001469178,0.00001334377,0.00304081,0.0006283627,0.00003178548,0.00003692783,0.00008417276,0.0001251513,0.0001225071,0.001358324,0.9943889,0.00002284436],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004657797,0.00005109139,0.00005571623,0.00006329706,0.00002114165,0.00001871641,0.9984749,0.0001285267,0.00114001],"genre_scores_gemma":[0.0002622832,0.00008091957,0.0003505673,0.0001396755,0.00001262878,0.0001981383,0.9970294,0.00006747292,0.001858731],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7063719,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808278003504818,"score_gpt":0.4201671747503836,"score_spread":0.4020843947153354,"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."}}