{"id":"W4231347957","doi":"10.1515/iupac.88.0672","title":"Deciduum","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":[],"consensus_categories":[],"category_scores_codex":[0.001318085,0.001311813,0.001424187,0.004490224,0.001249915,0.003548261,0.00231312,0.001716831,0.1548238],"category_scores_gemma":[0.01379418,0.0006299519,0.001693137,0.007725896,0.0005559286,0.002427989,0.0030289,0.001787419,0.1069379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001507487,"about_ca_system_score_gemma":0.003281403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01973735,"about_ca_topic_score_gemma":0.03227373,"domain_scores_codex":[0.9978725,0.000389055,0.0005265079,0.0005028856,0.0004764468,0.0002326743],"domain_scores_gemma":[0.9943683,0.002358506,0.0008184782,0.0009012324,0.001272647,0.0002808744],"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":[0.000128448,0.00001308864,0.001719653,0.002648485,0.00002875641,0.00005347846,0.00007247238,0.0001152627,0.00009254184,0.001513414,0.9814477,0.01216671],"study_design_scores_gemma":[0.00007117983,0.000008512959,0.00291501,0.001388084,0.00002147417,0.00009711082,0.0001198471,0.00006825038,0.00009711229,0.001296535,0.9938996,0.00001713849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001759522,0.0003338445,0.0001283594,0.000167754,0.00008335145,0.000032409,0.9956684,0.0001905857,0.003219377],"genre_scores_gemma":[0.0007874419,0.0004856763,0.0006363761,0.0003484085,0.00003528762,0.0002053768,0.9949579,0.0001305391,0.002413121],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1548238,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521442811406022,"score_gpt":0.4742004427904573,"score_spread":0.448986014676397,"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."}}