{"id":"W4413105994","doi":"10.1093/noajnl/vdaf123.109","title":"RMTD-03 SOCIOECONOMIC DISPARITIES IN CLINICAL TRIAL ENROLLMENT AMONG PATIENTS WITH BRAIN METASTASES: A CENTRAL PENNSYLVANIA CROSS-SECTIONAL ANALYSIS IN NEIGHBORHOOD-DISADVANTAGE METRICS","year":2025,"lang":"en","type":"article","venue":"Neuro-Oncology Advances","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Socioeconomic status; Cohort; Demography; Lung cancer; Internal medicine; Breast cancer; Subgroup analysis; Propensity score matching; Health equity; Decile; Cancer; Gerontology; Population; Public health; Confidence interval; Environmental health; Pathology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00148835,0.0003895242,0.001654018,0.001457282,0.0001546565,0.0001488853,0.0004823003,0.0003543064,0.0003417887],"category_scores_gemma":[0.001063999,0.0004232186,0.0004323878,0.001046281,0.0005328883,0.001259155,0.0001453475,0.0007190443,0.00005680348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009657923,"about_ca_system_score_gemma":0.0002647878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005660936,"about_ca_topic_score_gemma":0.006673108,"domain_scores_codex":[0.9952984,0.0001885674,0.002439402,0.001153475,0.00007449013,0.0008456068],"domain_scores_gemma":[0.9967821,0.001505771,0.00107737,0.0004104672,0.00005593997,0.0001683312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005206417,0.0008133838,0.9762011,0.0000212131,0.0002743561,0.00001526002,0.00007478016,0.003707947,4.218676e-7,0.01195083,0.0001495692,0.001584762],"study_design_scores_gemma":[0.02849434,0.0008056211,0.9496569,0.000007670134,0.00005943005,4.082382e-7,0.00004379129,0.0007932271,0.000002671651,0.007320634,0.01244219,0.0003731295],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886641,0.001572938,0.001045006,0.0004123063,0.002241935,0.0009254855,0.0004923755,0.00003302913,0.004612806],"genre_scores_gemma":[0.9963589,0.0009302335,0.000285878,0.001722888,0.0001687703,0.0001829082,0.0001026786,0.00002907788,0.0002186387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02654417,"threshold_uncertainty_score":0.999822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02134043062574332,"score_gpt":0.3257997190558735,"score_spread":0.3044592884301301,"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."}}