{"id":"W2883001605","doi":"10.1530/erc-18-0244","title":"Evaluating gastroenteropancreatic neuroendocrine tumors through microRNA sequencing","year":2018,"lang":"en","type":"article","venue":"Endocrine Related Cancer","topic":"Neuroendocrine Tumor Research Advances","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Southeastern Ontario Academic Medical Organization","keywords":"microRNA; Neuroendocrine tumors; Biology; Classifier (UML); Preprocessor; Computational biology; Artificial intelligence; Computer science; Genetics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001525717,0.000553027,0.0008117327,0.0002815442,0.0003113529,0.00006246634,0.0003601749,0.00001169422,0.002980378],"category_scores_gemma":[0.0007452584,0.0004910906,0.0002542285,0.000944014,0.0005138405,0.0004675516,0.0002815625,0.001005742,0.000537762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000675018,"about_ca_system_score_gemma":0.0004881185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007434994,"about_ca_topic_score_gemma":0.00007672264,"domain_scores_codex":[0.9951326,0.0002367004,0.0009242751,0.001036343,0.001000456,0.001669688],"domain_scores_gemma":[0.997735,0.000138997,0.0003100244,0.0008993857,0.0004712722,0.0004453371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00311506,0.00051274,0.07060147,0.001010648,0.001027061,0.04222272,0.0006958201,0.0005735628,0.846633,0.0007675652,0.01331114,0.01952917],"study_design_scores_gemma":[0.01721,0.009412315,0.00918997,0.002777878,0.0008715845,0.08111564,0.0006359653,0.005858589,0.8173649,0.001540248,0.05271999,0.001302886],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818538,0.001891251,0.00004942736,0.004019725,0.0006701121,0.001118135,0.00002378605,0.0005283201,0.009845463],"genre_scores_gemma":[0.9820125,0.0008063621,0.004126512,0.001426993,0.000810296,0.000240018,0.00003109371,0.0001832494,0.01036304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0614115,"threshold_uncertainty_score":0.9997541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05979104104869274,"score_gpt":0.4035878385768374,"score_spread":0.3437967975281446,"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."}}