{"id":"W2912244263","doi":"10.1016/j.ejca.2018.11.008","title":"Directional inconsistency between Response Evaluation Criteria in Solid Tumors (RECIST) time to progression and response speed and depth","year":2019,"lang":"en","type":"article","venue":"European Journal of Cancer","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fractal Systems (Canada)","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Medicine; Response Evaluation Criteria in Solid Tumors; Metric (unit); Hazard ratio; Consistency (knowledge bases); Oncology; Population; Internal medicine; Clinical trial; Statistics; Nuclear medicine; Mathematics; Confidence interval; Computer science; Artificial intelligence; Phases of clinical research","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":[],"consensus_categories":[],"category_scores_codex":[0.009922028,0.000148748,0.0003952407,0.0002660187,0.00004124533,0.00003745536,0.0001279187,0.00003203954,0.0005608156],"category_scores_gemma":[0.003954462,0.0001142643,0.00004290545,0.0001545174,0.00006943285,0.0001201036,0.00009573463,0.0002176819,0.0000690165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001337605,"about_ca_system_score_gemma":0.0001515548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.191226e-7,"about_ca_topic_score_gemma":0.000002422276,"domain_scores_codex":[0.9957607,0.002776373,0.0006894169,0.0001978691,0.0003955583,0.0001801245],"domain_scores_gemma":[0.997779,0.001283155,0.0003723304,0.0001499067,0.0002542323,0.000161352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.06933346,0.0006291533,0.1544894,0.0006293851,0.0005237751,0.0008701673,0.01278671,0.00003345052,0.558165,0.0004232083,0.01307485,0.1890414],"study_design_scores_gemma":[0.003309852,0.001703015,0.9798976,0.00183413,0.000147839,0.0003446744,0.0001225987,0.0003932827,0.004508624,0.005130074,0.00225433,0.0003539638],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953979,0.0003128971,0.00003589547,0.001155081,0.0001009617,0.0003481349,0.000008224576,0.00001181281,0.002629125],"genre_scores_gemma":[0.9938643,0.000006958985,0.004763712,0.00008353343,0.000125593,0.000003174398,6.751735e-7,0.00003039035,0.001121686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8254082,"threshold_uncertainty_score":0.6140537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04612288449131625,"score_gpt":0.3882236036217814,"score_spread":0.3421007191304652,"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."}}