{"id":"W4230383560","doi":"10.1515/iupac.87.0440","title":"Neurogenic","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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":[0.0009830302,0.001327929,0.00128186,0.003386489,0.0008438323,0.002770462,0.002051925,0.001495267,0.119344],"category_scores_gemma":[0.01106901,0.00050627,0.001884343,0.005888001,0.0003547617,0.001911387,0.001962986,0.001797495,0.08919015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001622079,"about_ca_system_score_gemma":0.003316649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02016461,"about_ca_topic_score_gemma":0.03534747,"domain_scores_codex":[0.9984963,0.0001876909,0.0003732502,0.00042955,0.000327572,0.0001855647],"domain_scores_gemma":[0.995946,0.001016441,0.0007133163,0.0008309206,0.001267444,0.0002259559],"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":[0.000319788,0.00002489563,0.004418054,0.003195865,0.00008507872,0.00005319664,0.00004061448,0.000205492,0.0001399033,0.001265403,0.9755777,0.0146741],"study_design_scores_gemma":[0.0002372597,0.00003128918,0.0110879,0.001895819,0.00009305809,0.0002122227,0.000109094,0.0001817773,0.0002261212,0.001948446,0.9839447,0.00003228389],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002741659,0.0003029957,0.0001072627,0.0001177222,0.00005325045,0.00003060373,0.9962376,0.0001465254,0.002729878],"genre_scores_gemma":[0.001063631,0.0004054657,0.0004324254,0.0002454099,0.00002773732,0.0001666169,0.9951921,0.00006973321,0.002396896],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.119344,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710877105545605,"score_gpt":0.4168490025594992,"score_spread":0.3997402315040432,"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."}}