{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008164361,0.001185466,0.001278005,0.003169808,0.0005366026,0.00213331,0.001621805,0.001379099,0.08793171],"category_scores_gemma":[0.009088004,0.0004288991,0.001606025,0.004245198,0.0003499333,0.001395014,0.001816575,0.00137453,0.06832004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001011259,"about_ca_system_score_gemma":0.002037403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009576281,"about_ca_topic_score_gemma":0.01564943,"domain_scores_codex":[0.9988056,0.000198689,0.0003534938,0.0003181834,0.0002032742,0.0001207524],"domain_scores_gemma":[0.99679,0.001026347,0.0006904338,0.0006342973,0.0006654464,0.000193538],"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":[0.0004996575,0.00002769218,0.006535808,0.006629406,0.0001544051,0.0001587789,0.0000550265,0.0004770414,0.0002987902,0.001325506,0.9540589,0.02977902],"study_design_scores_gemma":[0.0003140912,0.00004387571,0.01407798,0.002930098,0.0001351326,0.0005763557,0.0001053401,0.0003160989,0.0003411287,0.001960672,0.9791606,0.00003872424],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004528834,0.0008107863,0.0002115864,0.0001350207,0.00006227123,0.00005899383,0.9947681,0.0002450809,0.003255319],"genre_scores_gemma":[0.002060433,0.0008346173,0.0007519512,0.0003156008,0.00003976105,0.0002473945,0.9939255,0.00006731434,0.00175744],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08793171,"threshold_uncertainty_score":0,"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."}}