{"id":"W3182408363","doi":"10.21203/rs.3.rs-618303/v1","title":"Diagnostic Performance of MRI, SPECT, and PET in Detecting Renal Cell Carcinoma: A Meta-Analysis","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotel Dieu Hospital","funders":"Shanghai University of Medicine and Health Sciences; Shanghai Key Laboratory of Molecular Imaging; Shanghai Municipal Education Commission","keywords":"Diagnostic odds ratio; Meta-analysis; Medicine; Receiver operating characteristic; Nuclear medicine; Likelihood ratios in diagnostic testing; Positron emission tomography; Confidence interval; Renal cell carcinoma; Cochrane Library; Magnetic resonance imaging; Odds ratio; Single-photon emission computed tomography; Subgroup analysis; Spect imaging; Gold standard (test); Area under the curve; Radiology; Oncology; Internal medicine","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":[0.0167089,0.004011032,0.01822041,0.006632675,0.0009013754,0.004379177,0.002410958,0.003011391,0.002647052],"category_scores_gemma":[0.03416117,0.001967623,0.06043725,0.007155129,0.0007414618,0.002106422,0.001595763,0.002285741,0.0003462589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0017906,"about_ca_system_score_gemma":0.001574018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005656429,"about_ca_topic_score_gemma":0.008195011,"domain_scores_codex":[0.9868051,0.006831178,0.002723805,0.002011133,0.00123044,0.0003983706],"domain_scores_gemma":[0.9688146,0.02417099,0.003616217,0.00116928,0.001857833,0.0003712347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.003960208,0.00002518274,0.01526051,0.0466608,0.9289629,0.000131062,0.00003479141,0.0007669833,0.0002344356,0.0000409954,0.0002396698,0.003682371],"study_design_scores_gemma":[0.0002649147,0.00009846828,0.004593626,0.001775465,0.9925167,0.0000526377,0.00001498293,0.0002938189,0.00007513609,0.00006299446,0.0002379014,0.00001333854],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02790352,0.9682744,0.001443501,0.0003096817,0.0002660321,0.0002384608,0.001061837,0.00006344273,0.0004391699],"genre_scores_gemma":[0.6904695,0.3001715,0.00381194,0.0009982802,0.0006596345,0.001136767,0.002129161,0.00008931835,0.0005339634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01822041,"threshold_uncertainty_score":0.08836615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067518423596988,"score_gpt":0.3646465662211245,"score_spread":0.2578947238614256,"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."}}