{"id":"W4238187662","doi":"10.1515/iupac.79.1256","title":"Excipient","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; Organic chemistry; 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":[],"consensus_categories":[],"category_scores_codex":[0.001638661,0.001931673,0.001696127,0.005379292,0.0009552116,0.003469447,0.002845889,0.001913937,0.213044],"category_scores_gemma":[0.01384522,0.0006803637,0.001954752,0.00905283,0.0004737245,0.002278593,0.002546819,0.002143157,0.2778178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001545979,"about_ca_system_score_gemma":0.003093254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01367909,"about_ca_topic_score_gemma":0.0292408,"domain_scores_codex":[0.9976712,0.0004641214,0.0003972054,0.0007040651,0.0005330384,0.000230372],"domain_scores_gemma":[0.9947134,0.001750293,0.0005060833,0.001294251,0.001374423,0.0003614976],"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":[0.00005444129,0.00001098881,0.0004997512,0.0008927446,0.00002576212,0.00001481121,0.00001363473,0.0001253992,0.00006554628,0.0004197051,0.9937202,0.00415705],"study_design_scores_gemma":[0.0001179892,0.00001196678,0.001484679,0.0004558782,0.00002672813,0.00004869116,0.00003878009,0.0001631633,0.0001376167,0.001070011,0.996428,0.00001661457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005523718,0.0001080213,0.000104258,0.00008316396,0.00003719538,0.00001860964,0.9981085,0.0003418686,0.001143266],"genre_scores_gemma":[0.0001973747,0.000105599,0.0003809085,0.0001308253,0.00001475574,0.0001184986,0.9977863,0.0001385083,0.001127323],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.213044,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01775737793699741,"score_gpt":0.4278692033894875,"score_spread":0.4101118254524901,"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."}}