{"id":"W4236492908","doi":"10.1515/iupac.88.0930","title":"Ileum","year":2017,"lang":"tr","type":"dataset","venue":"IUPAC Standards Online","topic":"Intestinal and Peritoneal Adhesions","field":"Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001002348,0.001149816,0.001964454,0.0003422612,0.00107934,0.0002302225,0.001217667,0.0009958684,0.02251932],"category_scores_gemma":[0.004209907,0.0009424906,0.0006568498,0.0001906816,0.0007969313,0.0001565839,0.0005983635,0.002562532,0.0002880388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006943159,"about_ca_system_score_gemma":0.003105483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001263136,"about_ca_topic_score_gemma":0.001300832,"domain_scores_codex":[0.9941664,0.00007382566,0.001088667,0.001157349,0.002282718,0.001231073],"domain_scores_gemma":[0.9937304,0.0002307848,0.0008088682,0.002285013,0.001977734,0.0009671581],"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":[0.001282678,0.001303997,0.0003413954,0.001112383,0.0003540077,0.002154212,0.00005373833,6.514801e-7,0.00009042455,0.00007453471,0.9902355,0.002996496],"study_design_scores_gemma":[0.00221173,0.002504373,0.001447262,0.005626916,0.001315462,0.0006275844,0.0001272538,0.00006238907,0.00006027625,0.0002130546,0.9848525,0.0009512231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003053618,0.002731907,0.00001634381,0.00361223,0.003807549,0.00071988,0.9839906,0.0001181574,0.001949753],"genre_scores_gemma":[0.0007546441,0.002454038,0.0002472035,0.001108639,0.008826576,0.0000292935,0.9668772,0.0001248835,0.01957748],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02223128,"threshold_uncertainty_score":0.9997386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03215654003338612,"score_gpt":0.4634252636305678,"score_spread":0.4312687235971817,"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."}}