{"id":"W4244564650","doi":"10.1515/iupac.88.1188","title":"Peritoneum","year":2017,"lang":"sv","type":"dataset","venue":"IUPAC Standards Online","topic":"Intraperitoneal and Appendiceal Malignancies","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); Medicine; Computer science; Linguistics; Philosophy; Data mining","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","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.001138523,0.001531143,0.002703422,0.0003723382,0.001338217,0.0004772027,0.001531107,0.001390068,0.0166832],"category_scores_gemma":[0.001433495,0.001314088,0.0008060399,0.000213709,0.001409157,0.0002787931,0.0006607974,0.002419457,0.0001791978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000773777,"about_ca_system_score_gemma":0.003462337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001093527,"about_ca_topic_score_gemma":0.001029173,"domain_scores_codex":[0.9920855,0.0001721868,0.001371051,0.001520574,0.003053312,0.001797402],"domain_scores_gemma":[0.9934496,0.0001418945,0.00104623,0.00311697,0.001297472,0.0009477831],"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":[0.001250574,0.001297275,0.0001169754,0.002045342,0.0006000749,0.004279279,0.0001405978,0.000001027618,0.0007215735,0.00007367554,0.9848735,0.004600042],"study_design_scores_gemma":[0.002798746,0.002123892,0.0009693307,0.004932021,0.001413647,0.0006167448,0.0004646993,0.00003567243,0.0003252231,0.00006595719,0.9849355,0.001318526],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01113228,0.007627051,0.000008487843,0.004283168,0.005775271,0.00105276,0.9689991,0.0001499277,0.0009719513],"genre_scores_gemma":[0.005050229,0.005452539,0.00008898604,0.001396241,0.01006124,0.00004171999,0.9684436,0.0001775111,0.00928797],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.016504,"threshold_uncertainty_score":0.9999619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01948901352845031,"score_gpt":0.4300950337623313,"score_spread":0.410606020233881,"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."}}