{"id":"W4232744048","doi":"10.1515/iupac.87.0272","title":"Glioma","year":2016,"lang":"it","type":"dataset","venue":"IUPAC Standards Online","topic":"Animal testing and alternatives","field":"Veterinary","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009832365,0.001196237,0.001341785,0.0004308193,0.0004070461,0.0002154271,0.001288627,0.0006397849,0.01764237],"category_scores_gemma":[0.001782248,0.0009246014,0.0004853003,0.000375061,0.0005548345,0.0002439253,0.0008121324,0.001070938,0.0001398249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000674539,"about_ca_system_score_gemma":0.0008954087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002235885,"about_ca_topic_score_gemma":0.00006254956,"domain_scores_codex":[0.9939985,0.0003936056,0.001113424,0.001435786,0.00189334,0.001165299],"domain_scores_gemma":[0.9956893,0.0005913497,0.0008481409,0.001522918,0.0008798395,0.0004684486],"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":[0.002033722,0.0006934897,0.00006275766,0.0004086639,0.0004333438,0.003987129,0.00006200701,3.790626e-7,0.0006211405,0.00007128493,0.9813218,0.0103043],"study_design_scores_gemma":[0.001966164,0.004579101,0.0002290072,0.003288692,0.0002452636,0.0006219096,0.0001186184,0.00003172305,0.00007351946,0.0003515001,0.9872729,0.001221568],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01791845,0.001659778,0.0002469354,0.0006837636,0.001717195,0.0004095362,0.9763995,0.0002875724,0.0006772789],"genre_scores_gemma":[0.005445906,0.001028978,0.0002627707,0.0002390007,0.005815574,0.00002219918,0.98244,0.0001989819,0.004546614],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01750254,"threshold_uncertainty_score":0.9993204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08194864411247095,"score_gpt":0.4882024869821278,"score_spread":0.4062538428696569,"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."}}