{"id":"W4230058006","doi":"10.1515/iupac.88.1190","title":"Pharyngeal Groove","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","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":[0.0009010806,0.001268904,0.001235588,0.003725132,0.0007231251,0.002388755,0.00201627,0.001330502,0.1479518],"category_scores_gemma":[0.008392747,0.0005411684,0.001750724,0.004881923,0.0004711634,0.002139591,0.002485638,0.001465818,0.1208077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021577,"about_ca_system_score_gemma":0.002401111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01413011,"about_ca_topic_score_gemma":0.02466905,"domain_scores_codex":[0.9990084,0.0001408803,0.0002535601,0.0002967043,0.0001922976,0.0001082355],"domain_scores_gemma":[0.9967264,0.001064291,0.0005251935,0.0007080737,0.000812066,0.0001640662],"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":[0.0002121315,0.00001920985,0.002619928,0.003759683,0.00005147191,0.00007670609,0.00005667696,0.0002307801,0.0002585369,0.001066445,0.9690182,0.02263029],"study_design_scores_gemma":[0.00009129901,0.00001857867,0.008655933,0.001641973,0.00003942695,0.0001628994,0.0001151694,0.0001535797,0.0002484431,0.001391227,0.9874547,0.00002683446],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002671756,0.0003866901,0.0002282142,0.0001030459,0.00005540513,0.00004668278,0.9956021,0.0002736161,0.003036991],"genre_scores_gemma":[0.001341691,0.0006361526,0.0009559655,0.0002109356,0.00002841069,0.0002721633,0.9936585,0.0001055384,0.002790673],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1479518,"threshold_uncertainty_score":0.4949479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01913322416827311,"score_gpt":0.4281873799617234,"score_spread":0.4090541557934503,"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."}}