{"id":"W4238131632","doi":"10.1002/9780471420194.tnmc46.pub3","title":"Introductory Notes","year":2017,"lang":"en","type":"other","venue":"TNM Online","topic":"Ocular Oncology and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Section (typography); Computer science; Library science; Operating system","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00002708926,0.0001662467,0.0003734443,0.0001006397,0.00003269718,0.000003253613,0.00008554161,0.0003205159,0.01418388],"category_scores_gemma":[0.0001592538,0.0001284627,0.00007992242,0.0000167411,0.0001046089,0.00000826117,0.0000339554,0.0002077194,0.0011552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003381097,"about_ca_system_score_gemma":0.0001130418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006729225,"about_ca_topic_score_gemma":0.0002626785,"domain_scores_codex":[0.9994534,0.00001400367,0.00007277632,0.0002283943,0.0000946459,0.0001368267],"domain_scores_gemma":[0.9991415,0.00001914281,0.0001192211,0.0006325115,0.00001802545,0.00006955759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002978668,0.0003971947,0.002135061,0.00006639796,0.0003798702,0.0003695948,0.000007410522,7.082202e-9,0.0000226118,0.00001328534,0.9687755,0.02780327],"study_design_scores_gemma":[0.00103038,0.0001482415,0.004008048,0.0002805888,0.0003049648,0.00004032797,0.000001171184,9.568054e-7,0.00002974583,0.00001741844,0.9940409,0.00009724948],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004743,0.004901923,0.000007799732,0.002049116,0.001016633,0.0003911933,0.001305749,0.0002623567,0.9895909],"genre_scores_gemma":[0.0004962093,0.0003912716,0.002471769,0.0003321312,0.002896504,0.000007435438,0.003079775,0.0002141799,0.9901107],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02770602,"threshold_uncertainty_score":0.9996225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0254977758936167,"score_gpt":0.3465197900009578,"score_spread":0.3210220141073412,"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."}}