{"id":"W2983101271","doi":"10.1093/neuonc/noz175.328","title":"EPID-28. WHAT DO PATTERNS OF “UNCLASSIFIED” BRAIN TUMORS TELL US ABOUT INCIDENCE RATES OF NON-MALIGNANT BRAIN TUMORS IN CANADA?","year":2019,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Alberta","funders":"","keywords":"Incidence (geometry); Medicine; Population; Demography; Epidemiology; Disease; Pathology; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009353912,0.000245105,0.0003422049,0.002335086,0.0009389002,0.001322591,0.0008696018,0.0002618248,0.005643423],"category_scores_gemma":[0.005389553,0.0002439807,0.0006231884,0.005923036,0.0003351533,0.0003682333,0.0004891829,0.0004571512,0.0007842066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02201946,"about_ca_system_score_gemma":0.02926777,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9882317,"about_ca_topic_score_gemma":0.9895064,"domain_scores_codex":[0.9988317,0.000104413,0.0001091311,0.0001986717,0.0004234531,0.0003325738],"domain_scores_gemma":[0.9959156,0.0002584775,0.0006379973,0.0001623148,0.002599944,0.0004256789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001232706,0.00002237342,0.9497915,0.0002327774,0.0001312521,0.00005457012,0.0004296809,0.0003857928,0.0001247699,0.0009228481,0.02090896,0.02687224],"study_design_scores_gemma":[0.0000113928,0.00001367484,0.9880871,0.00009135852,0.00004109295,0.0000512577,0.0004384005,0.0004411105,0.0001175183,0.0001260838,0.01056789,0.00001317523],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.4307987,0.004970288,0.001519979,0.00572069,0.0001201219,0.0002232755,0.5117335,0.000263022,0.04465053],"genre_scores_gemma":[0.875607,0.0027428,0.001540188,0.0007562912,0.00003132394,0.0001233423,0.1103893,0.00005602873,0.008753793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02201946,"threshold_uncertainty_score":0.159763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01064102031609406,"score_gpt":0.2937611091257089,"score_spread":0.2831200888096148,"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."}}