{"id":"W4242214679","doi":"10.1515/iupac.79.1861","title":"Promotor","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Library science; Chemistry; Philosophy; Biology; Linguistics","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":[0.00141122,0.001304193,0.001474189,0.004193334,0.001089509,0.003196876,0.00190352,0.001493637,0.4337489],"category_scores_gemma":[0.01296099,0.0006082359,0.001130126,0.008128587,0.0003255677,0.002552256,0.002127209,0.001407629,0.4526769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001406715,"about_ca_system_score_gemma":0.003295303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01851167,"about_ca_topic_score_gemma":0.03347366,"domain_scores_codex":[0.9983882,0.0002860259,0.000236641,0.0005160195,0.0003364573,0.0002366805],"domain_scores_gemma":[0.9943553,0.001484119,0.0005747725,0.00107895,0.001838595,0.0006682469],"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":[0.0000563761,0.00000859662,0.0005801197,0.0004637791,0.000008422357,0.000007406326,0.00001452386,0.00002731557,0.00002777509,0.0003050562,0.9935144,0.004986089],"study_design_scores_gemma":[0.000111619,0.000009926415,0.002062297,0.0003096546,0.00001334123,0.00002225636,0.00006447218,0.00005215618,0.000075247,0.0005773755,0.9966908,0.00001090673],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006810122,0.00007531392,0.00005790035,0.0001119973,0.00004654004,0.00002617495,0.9958273,0.0002229614,0.003563663],"genre_scores_gemma":[0.0004894775,0.0001932603,0.0004240008,0.0003629885,0.00005214716,0.0002733411,0.9899834,0.0002178683,0.008003348],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.566251,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01682114737872643,"score_gpt":0.4243109164934516,"score_spread":0.4074897691147252,"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."}}