{"id":"W4251090870","doi":"10.1515/iupac.88.1030","title":"Meninx","year":2017,"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; Terminology; Relation (database); Computer science; Linguistics; Data mining; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002002549,0.001576411,0.00167637,0.004930692,0.001066563,0.004741469,0.002603718,0.001925445,0.304126],"category_scores_gemma":[0.0197733,0.0008213534,0.001604457,0.01060003,0.0005038622,0.003451033,0.003634605,0.002096867,0.287581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001681995,"about_ca_system_score_gemma":0.003747295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01161953,"about_ca_topic_score_gemma":0.02115328,"domain_scores_codex":[0.9974718,0.0005389993,0.0005920449,0.0006775472,0.0004890782,0.0002305182],"domain_scores_gemma":[0.9929438,0.002543981,0.0009705538,0.001327195,0.001777289,0.0004371953],"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":[0.00006253464,0.000008030568,0.0004981607,0.001750984,0.00002135369,0.00001247079,0.00002926853,0.00007679535,0.00005980143,0.0007965259,0.9931692,0.003514763],"study_design_scores_gemma":[0.0001087976,0.00000996672,0.001324505,0.0009062046,0.00001674981,0.00002613277,0.00005150372,0.00006660572,0.0000849771,0.0009914669,0.9963971,0.0000160473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003810475,0.0001013881,0.00006269076,0.0001202783,0.00003471297,0.00002183034,0.99797,0.0002039757,0.001446947],"genre_scores_gemma":[0.0002181618,0.000197862,0.0003753158,0.0001989054,0.00002287062,0.0002145846,0.9968924,0.0001631977,0.001716693],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.695874,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0250096783707101,"score_gpt":0.4750824429167627,"score_spread":0.4500727645460526,"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."}}