{"id":"W3165196335","doi":"10.6004/jnccn.2020.7666","title":"Risk of Cancer-Specific Death for Patients Diagnosed With Neuroendocrine Tumors: A Population-Based Analysis","year":2021,"lang":"en","type":"article","venue":"Journal of the National Comprehensive Cancer Network","topic":"Neuroendocrine Tumor Research Advances","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Manitoba; Health Sciences Centre; Occupational Cancer Research Centre; Manitoba Health; University of Toronto; Sunnybrook Health Science Centre","funders":"Ontario Ministry of Health and Long-Term Care; EMD Serono; Ipsen; Ipsen Biopharmaceuticals","keywords":"Medicine; Interquartile range; Cancer; Internal medicine; Population; Hazard ratio; Cause of death; Oncology; Cohort; Colorectal cancer; Proportional hazards model; Cohort study; Disease; Confidence interval; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00007639254,0.0001866313,0.0006465319,0.0002280787,0.0001540718,0.00002180916,0.0002199099,0.000007974392,0.00009453559],"category_scores_gemma":[0.000580129,0.0001223185,0.0004932944,0.00147053,0.00006582956,0.0001004605,0.00004934803,0.0003610339,2.570891e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003179763,"about_ca_system_score_gemma":0.0006618998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001112483,"about_ca_topic_score_gemma":0.0002363609,"domain_scores_codex":[0.9972664,0.0002123258,0.0006443348,0.0002381621,0.001341101,0.0002977424],"domain_scores_gemma":[0.9909235,0.001221046,0.001134233,0.0001982765,0.00638032,0.0001425999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00132349,0.0001765922,0.6816166,0.00005712196,0.0008951199,0.00009057806,0.000006950197,0.3129134,0.00008792659,0.00004227445,0.002480115,0.000309801],"study_design_scores_gemma":[0.004419322,0.0005160783,0.9823014,0.0003789268,0.001037268,0.00006503885,0.00001932787,0.002415252,0.001125507,0.0003547012,0.007251733,0.0001154594],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926397,0.00420338,0.0002195915,0.001751887,0.0003651344,0.0005378617,0.0002508343,0.000007746839,0.00002381888],"genre_scores_gemma":[0.9953615,0.0008461617,0.001992316,0.0008975011,0.0006950723,0.00005883684,0.00003852621,0.00002909142,0.0000809897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3104981,"threshold_uncertainty_score":0.4988003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03210202073306971,"score_gpt":0.3430044523649968,"score_spread":0.310902431631927,"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."}}