{"id":"W4233050242","doi":"10.1515/iupac.87.0367","title":"Meninx","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; 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":[0.001579448,0.001592134,0.001486179,0.003937196,0.0009218393,0.004273243,0.002445363,0.001846244,0.2566966],"category_scores_gemma":[0.01519534,0.0007102248,0.001402077,0.00819838,0.0004626367,0.002943023,0.003178905,0.001888062,0.2678899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510632,"about_ca_system_score_gemma":0.003075811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009706845,"about_ca_topic_score_gemma":0.01892468,"domain_scores_codex":[0.9980223,0.0004027153,0.0004146011,0.0006051997,0.0003565986,0.0001986217],"domain_scores_gemma":[0.9951103,0.001667385,0.000656536,0.001047341,0.001135799,0.000382575],"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":[0.00007909638,0.00000965695,0.0006647108,0.001390924,0.00002215462,0.00001426973,0.00002466911,0.0001045883,0.00006877008,0.0006922467,0.9933919,0.003536978],"study_design_scores_gemma":[0.0001427047,0.0000134174,0.001471487,0.0006197657,0.0000175669,0.00003396727,0.00004827967,0.000115676,0.00011404,0.001151961,0.9962549,0.00001610432],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005061863,0.00009659679,0.0000611831,0.000111938,0.0000326964,0.00001895277,0.9981418,0.0002527311,0.001233484],"genre_scores_gemma":[0.0002773795,0.0001577756,0.000378892,0.0001739106,0.0000202801,0.0001621062,0.9971989,0.0001440759,0.001486635],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2566966,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673123230772497,"score_gpt":0.4301871295368649,"score_spread":0.4134558972291399,"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."}}