{"id":"W4220770313","doi":"10.1016/j.esmoop.2022.100413","title":"“The first ones now, will later be last”: understanding the importance of historical context when reading ESMO-MCBS scores","year":2022,"lang":"en","type":"editorial","venue":"ESMO Open","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Genentech; Ipsen; Servier; Nordic Nanovector; Radius Health; Merck KGaA; FibroGen; Gilead Sciences; Amgen; Ariad Pharmaceuticals; Chugai Pharmaceutical; Roche; Meso Scale Diagnostics; Sanofi; Merck; Pfizer; G1 Therapeutics; Bayer; Shire; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb","keywords":"Pazopanib; Medicine; Sunitinib; Axitinib; Cabozantinib; Renal cell carcinoma; Pembrolizumab; Internal medicine; Oncology; Nivolumab; Context (archaeology); Tyrosine-kinase inhibitor; Cancer; Immunotherapy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009621109,0.001788917,0.003034916,0.006421874,0.003025662,0.01003856,0.003078075,0.0109418,0.02023274],"category_scores_gemma":[0.07128002,0.0008963101,0.001611185,0.003692995,0.002978034,0.006819445,0.002312114,0.01277622,0.01092876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003731501,"about_ca_system_score_gemma":0.005736626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005797517,"about_ca_topic_score_gemma":0.01780846,"domain_scores_codex":[0.9945949,0.001460997,0.001040204,0.0003323505,0.002227007,0.0003446401],"domain_scores_gemma":[0.9469945,0.03049363,0.002052073,0.0008585848,0.01664653,0.002954637],"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":[0.00001024038,0.000002601515,0.00001643951,0.0002030154,0.000008073528,0.00002745823,0.00002168228,0.000007546349,0.000008450034,0.0002514029,0.9961131,0.003330063],"study_design_scores_gemma":[0.00005098709,0.00001674878,0.0003861068,0.002441409,0.0000699281,0.000173082,0.0001496509,0.00008124444,0.0000679041,0.001858988,0.9946783,0.00002585145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00006253551,0.01028247,0.0001394393,0.1008704,0.88504,0.0000262109,0.0001996514,0.00006627826,0.00331309],"genre_scores_gemma":[0.001097647,0.01405021,0.0001876177,0.0470982,0.9283658,0.00004394847,0.0001356498,0.0001059883,0.008914873],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02023274,"threshold_uncertainty_score":0.06768525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05402991100113508,"score_gpt":0.2882864576658172,"score_spread":0.2342565466646821,"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."}}