{"id":"W2947154035","doi":"10.1200/jco.2019.37.15_suppl.2585","title":"Measuring the long-term “tail of curve” survival benefits in oncology trials: A comparison of the ASCO Value Framework and the ESMO Magnitude of Clinical Benefit Scale.","year":2019,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Oncology; Internal medicine; Clinical trial; Randomized controlled trial; Immunotherapy; Clinical Oncology; Cancer","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3865714,0.001084308,0.003921261,0.01723814,0.0009890265,0.005135088,0.002237058,0.00176897,0.002645516],"category_scores_gemma":[0.6510356,0.0006133819,0.006746616,0.01810462,0.003300834,0.005561111,0.007439051,0.002510844,0.0002741421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005855582,"about_ca_system_score_gemma":0.005623142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654303,"about_ca_topic_score_gemma":0.003617538,"domain_scores_codex":[0.5861365,0.3061337,0.04485409,0.008086797,0.05251916,0.002269689],"domain_scores_gemma":[0.2469443,0.6458957,0.06747703,0.01529311,0.02182115,0.002568675],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.01590464,0.0004367085,0.3568411,0.04005466,0.03799253,0.0002447111,0.007332805,0.01514075,0.0009745031,0.04581765,0.01595142,0.4633086],"study_design_scores_gemma":[0.005119926,0.007170042,0.6963571,0.02701329,0.01507541,0.001002411,0.006589735,0.05743098,0.002015297,0.1199705,0.06130439,0.0009508159],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5209429,0.1692818,0.199751,0.0165471,0.002593252,0.02163901,0.01667342,0.0005208405,0.05205073],"genre_scores_gemma":[0.9277593,0.004220368,0.05515228,0.001449443,0.0003655709,0.008261306,0.002371868,0.00005057448,0.0003692471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6134286,"threshold_uncertainty_score":0.7564667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3083587440940593,"score_gpt":0.4576854135794311,"score_spread":0.1493266694853718,"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."}}