{"id":"W7084032768","doi":"10.1109/seai65851.2025.11108907","title":"Detection of Renal Cell Carcinoma Based on Clinical Data Using Machine Learning Approach","year":2025,"lang":"en","type":"article","venue":"","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McMaster University","funders":"","keywords":"Random forest; Support vector machine; Renal cell carcinoma; Principal component analysis; Feature extraction; Ensemble learning; Feature (linguistics); Pattern recognition (psychology)","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":[0.001398784,0.0004156738,0.0007722927,0.00341177,0.0001991995,0.0009996026,0.0005201668,0.0007722136,0.0007639523],"category_scores_gemma":[0.005813166,0.000167077,0.000460375,0.001610603,0.0001926084,0.0006840488,0.0003979964,0.0004905858,0.0003631946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005498024,"about_ca_system_score_gemma":0.0005622957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002735824,"about_ca_topic_score_gemma":0.002455511,"domain_scores_codex":[0.999019,0.0003645752,0.0000929965,0.0001602153,0.0002815429,0.0000816334],"domain_scores_gemma":[0.9973289,0.001496919,0.0003788878,0.0001439741,0.0005270149,0.0001243359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008484511,0.0006016371,0.5395243,0.0002241264,0.0002610968,0.0005772216,0.00006308506,0.1081338,0.007563497,0.002200734,0.00479879,0.3352034],"study_design_scores_gemma":[0.00002521837,0.0001748246,0.07969292,0.00003897287,0.00006089234,0.0003472687,0.00008572132,0.9106098,0.004344319,0.003176561,0.001411419,0.0000321673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8033872,0.003605911,0.182376,0.002311499,0.0001510986,0.000251983,0.003423586,0.0008377907,0.003654914],"genre_scores_gemma":[0.9765935,0.0003512038,0.02128187,0.00007191353,0.00006495074,0.00003713123,0.001229545,0.000008243532,0.0003616662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00341177,"threshold_uncertainty_score":0.007397592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.162186769272797,"score_gpt":0.2798742433031947,"score_spread":0.1176874740303976,"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."}}