{"id":"W1999879391","doi":"10.1016/j.eururo.2006.07.021","title":"Initial Biopsy Outcome Prediction—Head-to-Head Comparison of a Logistic Regression-Based Nomogram versus Artificial Neural Network","year":2006,"lang":"en","type":"article","venue":"European Urology","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Nomogram; Medicine; Prostate cancer; Logistic regression; Biopsy; Rectal examination; Prostate; Radiology; Oncology; Cancer; 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":[0.009061698,0.001286326,0.003663063,0.000947193,0.000511545,0.001224205,0.001293298,0.001344511,0.003988435],"category_scores_gemma":[0.0167719,0.000437521,0.003084774,0.0006432576,0.0006698923,0.001689628,0.001160451,0.001490089,0.001209596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007007789,"about_ca_system_score_gemma":0.0009106607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005243565,"about_ca_topic_score_gemma":0.005961343,"domain_scores_codex":[0.9978759,0.001388056,0.00009366579,0.0003384415,0.0001510939,0.0001529403],"domain_scores_gemma":[0.9883463,0.008414416,0.0009140737,0.0008280005,0.0007162034,0.0007809544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.4361998,0.001533211,0.260214,0.001361586,0.01566744,0.000422316,0.0004062299,0.04231101,0.003266415,0.0003889237,0.008046846,0.2301822],"study_design_scores_gemma":[0.01802301,0.06489195,0.6302568,0.0004854533,0.02281736,0.00129076,0.001195765,0.2439848,0.008670394,0.002764517,0.005033363,0.0005858821],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825343,0.005252826,0.006132467,0.0006117656,0.0009267103,0.0001874446,0.002006409,0.0003246226,0.002023498],"genre_scores_gemma":[0.9947224,0.0006649451,0.001408211,0.0002289292,0.0002911603,0.00005870983,0.001592755,0.00006304871,0.0009700254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009061698,"threshold_uncertainty_score":0.04792339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1131272437343739,"score_gpt":0.382373742481781,"score_spread":0.269246498747407,"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."}}