{"id":"W4392810267","doi":"10.53555/sfs.v10i6.2266","title":"Role Of Multidetector CT In Characterization Of Renal Mass","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Renal mass; Characterization (materials science); Multidetector computed tomography; Radiology; Medicine; Internal medicine; Computed tomography; Kidney; Materials science; Nanotechnology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002071196,0.0004617621,0.000678997,0.002734368,0.0002180072,0.001380392,0.0006743887,0.0008292711,0.001013952],"category_scores_gemma":[0.00394685,0.0002227931,0.0004596673,0.001167279,0.0007621522,0.00171092,0.0005359662,0.001363428,0.0005249825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005860201,"about_ca_system_score_gemma":0.0008540062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001768189,"about_ca_topic_score_gemma":0.002020849,"domain_scores_codex":[0.9992164,0.0002673926,0.0001119646,0.0001038515,0.0002537765,0.00004650214],"domain_scores_gemma":[0.9985482,0.0006770889,0.0001877325,0.00005697526,0.0004464789,0.00008342147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002417821,0.00008968275,0.06039403,0.003211043,0.0002090628,0.005186881,0.0005393115,0.00195378,0.01565374,0.005046897,0.01524777,0.8922261],"study_design_scores_gemma":[0.00008723541,0.000944858,0.155489,0.01082593,0.001093567,0.1644858,0.002814505,0.01613797,0.03061805,0.01499297,0.6020688,0.0004413741],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0217768,0.9353749,0.02191759,0.00597337,0.0007457539,0.00005673767,0.0001377214,0.0001752407,0.01384183],"genre_scores_gemma":[0.1479144,0.806985,0.03696811,0.002297208,0.003047689,0.00004987565,0.0002209445,0.00008577316,0.002431122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002734368,"threshold_uncertainty_score":0.01095366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.12729209595541,"score_gpt":0.2834148883800751,"score_spread":0.1561227924246651,"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."}}