{"id":"W4248697327","doi":"10.1515/iupac.79.0974","title":"Carrier","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","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":[0.001582542,0.001891876,0.001561661,0.004093066,0.001141739,0.003926343,0.003255012,0.002094832,0.2151124],"category_scores_gemma":[0.01313314,0.0006482324,0.001766413,0.007594349,0.0004064241,0.003345835,0.002639123,0.001773491,0.3125916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00180221,"about_ca_system_score_gemma":0.003459461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02386708,"about_ca_topic_score_gemma":0.03637434,"domain_scores_codex":[0.9975992,0.0003808632,0.0003804501,0.0008331675,0.0005101711,0.0002961663],"domain_scores_gemma":[0.9945592,0.001263898,0.0004951193,0.001560298,0.001772668,0.000348675],"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":[0.00007830717,0.00001259211,0.0006974405,0.0005615787,0.00002301054,0.00001365563,0.00001845222,0.0001117444,0.00006387864,0.0007177491,0.9924828,0.005218806],"study_design_scores_gemma":[0.0001074322,0.0000123816,0.001666173,0.000371311,0.00002373494,0.00004265202,0.00007562815,0.0001870997,0.0001464402,0.001562988,0.9957845,0.00001959516],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007728837,0.00008235163,0.0001198962,0.00009384665,0.00003709781,0.00002311432,0.9973943,0.000350153,0.001821999],"genre_scores_gemma":[0.0002787337,0.00008863358,0.000324291,0.0001395557,0.00001166193,0.0001055231,0.99737,0.0001016644,0.001579793],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2151124,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01563777775115206,"score_gpt":0.4177166573669129,"score_spread":0.4020788796157609,"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."}}