{"id":"W4235345770","doi":"10.1515/iupac.87.0203","title":"Dysaphia","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Psychology; Chemistry; Linguistics; Philosophy; Data mining; 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":[],"consensus_categories":[],"category_scores_codex":[0.000855645,0.001433426,0.001097427,0.003502446,0.0007486626,0.002589472,0.001902863,0.001354628,0.1062902],"category_scores_gemma":[0.00937285,0.0004688283,0.001434369,0.004304537,0.0003394741,0.001746743,0.002204006,0.001445446,0.1139234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001326967,"about_ca_system_score_gemma":0.002494097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01314725,"about_ca_topic_score_gemma":0.03161445,"domain_scores_codex":[0.9988594,0.0001707574,0.0002567665,0.0003493077,0.0002279892,0.0001358059],"domain_scores_gemma":[0.9971737,0.0007698163,0.0004437479,0.0006314946,0.0007652828,0.0002159186],"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":[0.0001537929,0.00002025577,0.00233387,0.001590511,0.00004105588,0.00003011063,0.00002800537,0.0001303383,0.00008886991,0.0006026809,0.9867617,0.008218776],"study_design_scores_gemma":[0.0001971819,0.00002520409,0.008669986,0.0008093691,0.0000460387,0.000124809,0.0000823779,0.0002184397,0.0002362627,0.001378691,0.9881825,0.00002923042],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000225913,0.0001645004,0.00008020941,0.0001000183,0.00004323607,0.00002875894,0.9972024,0.000301598,0.00185338],"genre_scores_gemma":[0.000735425,0.0001971685,0.0003625954,0.0001508861,0.00001988956,0.0001841396,0.9964132,0.00006632048,0.001870343],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1062902,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210286876138556,"score_gpt":0.3870691231199999,"score_spread":0.3749662543586144,"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."}}