{"id":"W2460314666","doi":"10.1158/1538-7755.disp14-b58","title":"Abstract B58: Underserved populations in kidney cancer research and treatment","year":2015,"lang":"en","type":"article","venue":"Cancer Epidemiology Biomarkers & Prevention","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kidney cancer; Medicine; Cancer; Kidney; Kidney disease; Disease; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005992477,0.0002008894,0.0006099127,0.001399262,0.00286962,0.003088927,0.001152219,0.002495106,0.03532513],"category_scores_gemma":[0.01738944,0.000264644,0.0005499437,0.00227084,0.0009177112,0.00273105,0.004503009,0.002781867,0.003513572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003020689,"about_ca_system_score_gemma":0.01502026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01909325,"about_ca_topic_score_gemma":0.02193258,"domain_scores_codex":[0.9957469,0.001755805,0.000373615,0.0002117199,0.0009231412,0.0009889314],"domain_scores_gemma":[0.9688104,0.003442588,0.003704016,0.000895543,0.003603857,0.01954351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001978201,0.0006255072,0.2562049,0.0009405431,0.00006541901,0.0006794886,0.001625001,0.0001081195,0.0005057554,0.008181496,0.5619383,0.1689276],"study_design_scores_gemma":[0.0002871796,0.0005309034,0.7442053,0.003190066,0.00009883669,0.0009228056,0.009134625,0.0005220891,0.0002341883,0.008684467,0.2320998,0.00008961721],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1516672,0.01987666,0.000684917,0.7214733,0.007922141,0.0007934401,0.007414831,0.0002746693,0.08989275],"genre_scores_gemma":[0.646314,0.02665864,0.002489937,0.2770533,0.01475148,0.001687561,0.005642518,0.0001444677,0.02525809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03532513,"threshold_uncertainty_score":0.1181744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5217126686830379,"score_gpt":0.50391905887323,"score_spread":0.01779360980980793,"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."}}