{"id":"W4249103377","doi":"10.1515/iupac.88.1154","title":"Orofacial Cleft","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Delphi Technique in Research","field":"Social Sciences","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00145502,0.001039804,0.00144396,0.005151215,0.0006977315,0.001462667,0.001697763,0.001239289,0.09276281],"category_scores_gemma":[0.01098235,0.0004844827,0.001381865,0.006316061,0.000405007,0.001497196,0.001873832,0.001455366,0.03579321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001192976,"about_ca_system_score_gemma":0.002828276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01230713,"about_ca_topic_score_gemma":0.02409332,"domain_scores_codex":[0.9982298,0.0002262527,0.000687443,0.0003537054,0.0003641736,0.0001386862],"domain_scores_gemma":[0.9960872,0.001298527,0.0008694992,0.0007043834,0.0008552588,0.000185049],"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":[0.0002479952,0.00003421732,0.008465993,0.005267685,0.0001129031,0.0002455564,0.0001071556,0.0001824322,0.0001859878,0.001752796,0.9532763,0.03012091],"study_design_scores_gemma":[0.0002529053,0.00003351095,0.04712943,0.008552548,0.0001122327,0.001350542,0.0005025807,0.0001981551,0.0003401818,0.00320841,0.9382458,0.00007377885],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007622144,0.0006025709,0.0002038753,0.0001201683,0.00004953593,0.000130593,0.9942062,0.00006916842,0.003855685],"genre_scores_gemma":[0.002355974,0.001092316,0.0009232381,0.0002381771,0.0000236093,0.0009123141,0.9923125,0.00004926169,0.002092612],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9072372,"threshold_uncertainty_score":0.3103225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08960135789080897,"score_gpt":0.5838882497956677,"score_spread":0.4942868919048587,"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."}}