{"id":"W4247059702","doi":"10.1515/iupac.88.0611","title":"Cleft","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cleft Lip and Palate Research","field":"Biochemistry, Genetics and Molecular Biology","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":[0.001189768,0.001146382,0.001327984,0.00413292,0.0008121182,0.002627211,0.002385365,0.001648681,0.1740157],"category_scores_gemma":[0.01081108,0.000530231,0.001562963,0.005917957,0.0004045629,0.00221501,0.002791865,0.001391614,0.1395795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001296479,"about_ca_system_score_gemma":0.002921381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01318626,"about_ca_topic_score_gemma":0.02349233,"domain_scores_codex":[0.9983909,0.0002419143,0.0004293192,0.0004499645,0.0003292976,0.0001586312],"domain_scores_gemma":[0.9966295,0.0009432105,0.0005477428,0.0008082427,0.0008541708,0.0002170201],"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":[0.0001690299,0.00001654127,0.002435441,0.002803886,0.00005546863,0.00009047448,0.00004878699,0.0001091764,0.0001536615,0.001480751,0.9769648,0.01567184],"study_design_scores_gemma":[0.000111493,0.00001377633,0.006055921,0.001795413,0.00004578188,0.0002627652,0.0001288024,0.0000906917,0.0002186334,0.001704134,0.9895482,0.00002437094],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002214845,0.0003232679,0.0001395084,0.0001219686,0.00005114344,0.00003514065,0.9957787,0.0001759378,0.003152922],"genre_scores_gemma":[0.0006869353,0.0004050662,0.0004303767,0.0002402718,0.00001639159,0.0001466682,0.9955463,0.0000770898,0.002450904],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1740157,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02075077712423932,"score_gpt":0.4462378820196365,"score_spread":0.4254871048953972,"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."}}