{"id":"W4366351362","doi":"10.1007/s00330-023-09551-x","title":"Predicting the recurrence risk of renal cell carcinoma after nephrectomy: potential role of CT-radiomics for adjuvant treatment decisions","year":2023,"lang":"en","type":"article","venue":"European Radiology","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; Sinai Health System; Lunenfeld-Tanenbaum Research Institute; University of Toronto; University Health Network","funders":"Royal College of Surgeons in Ireland; Deutsche Forschungsgemeinschaft; Ontario Institute for Cancer Research","keywords":"Medicine; Renal cell carcinoma; Nephrectomy; Hazard ratio; Stage (stratigraphy); Internal medicine; Adjuvant therapy; Proportional hazards model; Kidney cancer; Oncology; Radiomics; Neuroradiology; Radiology; Cancer; Kidney; Confidence interval","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001929454,0.0004609375,0.0006605743,0.001074141,0.0002414169,0.001511593,0.0004926381,0.0007304504,0.002172918],"category_scores_gemma":[0.01118186,0.0001990506,0.0005614068,0.0007643852,0.0003731782,0.0008967573,0.0003967143,0.0008047643,0.0003282214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004339537,"about_ca_system_score_gemma":0.000643974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002256675,"about_ca_topic_score_gemma":0.00432013,"domain_scores_codex":[0.9993024,0.0003661251,0.00008842458,0.0000628283,0.000114246,0.00006597443],"domain_scores_gemma":[0.9964646,0.002187056,0.0006230546,0.0001328722,0.0003252855,0.0002671106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001149316,0.0001657179,0.922787,0.00008647361,0.0002169752,0.0003653931,0.00007052335,0.003450504,0.0009213038,0.0004782288,0.0008900549,0.06941859],"study_design_scores_gemma":[0.0001620882,0.001197961,0.9189675,0.0003129121,0.001245415,0.002944203,0.0005925877,0.05727134,0.003272051,0.005089782,0.008851005,0.00009310368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702387,0.01248599,0.004368991,0.003018898,0.000147792,0.00004172768,0.0004374474,0.00005937201,0.009201053],"genre_scores_gemma":[0.9959475,0.001300735,0.001722959,0.000147979,0.0001578923,0.000008430272,0.0001916523,0.00001083848,0.0005120878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002256675,"threshold_uncertainty_score":0.01020402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01978199501265759,"score_gpt":0.2445242367684244,"score_spread":0.2247422417557668,"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."}}