{"id":"W1575433014","doi":"10.1002/cncr.29099","title":"Exploring the rising incidence of neuroendocrine tumors: A population‐based analysis of epidemiology, metastatic presentation, and outcomes","year":2014,"lang":"en","type":"article","venue":"Cancer","topic":"Neuroendocrine Tumor Research Advances","field":"Medicine","cited_by":855,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre","funders":"Ontario Institute for Cancer Research","keywords":"Medicine; Incidence (geometry); Epidemiology; Population; Retrospective cohort study; Cohort; Neuroendocrine tumors; Cohort study; Presentation (obstetrics); Internal medicine; Pediatrics; Demography; Surgery; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009215254,0.0001779371,0.0002537332,0.001296592,0.0003209845,0.0005746133,0.0003989006,0.0002879078,0.0006814523],"category_scores_gemma":[0.002105648,0.0002080362,0.0004637831,0.002072717,0.0002739376,0.0005118098,0.0005433174,0.0004136064,0.0001262001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008674866,"about_ca_system_score_gemma":0.0009271185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04519949,"about_ca_topic_score_gemma":0.05673362,"domain_scores_codex":[0.9994978,0.00009395323,0.00005168031,0.0001294968,0.0001365381,0.00009046774],"domain_scores_gemma":[0.9984042,0.0001906412,0.0007837442,0.0001157065,0.0002798483,0.0002258884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001032037,0.000002870232,0.9996133,0.000002334921,0.0000173604,0.00001474369,0.00001413211,0.00001276852,0.00002594292,0.000003088486,0.000022571,0.000260554],"study_design_scores_gemma":[0.000001434864,0.00002055126,0.9995832,0.00000270884,0.00001664663,0.0001004777,0.00008149152,0.0000936043,0.00001446281,0.000007831325,0.00007619119,0.000001503135],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986621,0.0002500678,0.0001079165,0.00004688542,0.000002392243,0.000008414802,0.00073612,0.000002682235,0.0001832892],"genre_scores_gemma":[0.9990591,0.000171216,0.00009976727,0.00001405488,0.000005158612,0.00000694287,0.0006058134,0.00000101348,0.0000370318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04519949,"threshold_uncertainty_score":0.08987278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1351138466823844,"score_gpt":0.4237649881002987,"score_spread":0.2886511414179143,"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."}}