{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003348187,0.000106606,0.0006180116,0.0003287107,0.00004660719,0.000004191836,0.0001060678,0.000001571171,0.00004472267],"category_scores_gemma":[0.004726131,0.00006856993,0.0001128359,0.0007478769,0.0001750043,0.0001569954,0.00005285726,0.0001170388,3.952889e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002593953,"about_ca_system_score_gemma":0.00003802298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001905962,"about_ca_topic_score_gemma":0.0002911606,"domain_scores_codex":[0.9984915,0.0003319152,0.000488248,0.0002232365,0.0002500284,0.0002150646],"domain_scores_gemma":[0.9970064,0.002137858,0.0002805946,0.0003472932,0.0001445146,0.00008337617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006310496,0.00002288478,0.9887821,0.0001657311,0.0002162815,0.00001658356,0.00004128708,0.006856561,0.0006770072,0.0002597304,0.00001760294,0.002881125],"study_design_scores_gemma":[0.0004649254,0.00009484986,0.9824296,0.0000711356,0.0006416541,0.00001622272,0.00006631209,0.01238916,0.003412786,0.0002508771,0.0001135927,0.00004885189],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995638,0.0003963981,0.0007380096,0.00286536,0.00004354055,0.0002671259,0.0000134781,0.00001528505,0.00002278825],"genre_scores_gemma":[0.9980198,0.0001496153,0.001267196,0.0003789052,0.00002071528,0.00009313753,0.00001138095,0.00001162742,0.0000475782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006352465,"threshold_uncertainty_score":0.5657962,"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."}}