{"id":"W2128165053","doi":"10.1002/pros.21159","title":"Predictive models before and after radical prostatectomy","year":2010,"lang":"en","type":"review","venue":"The Prostate","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Prostatectomy; Nomogram; Medicine; Decision tree; Context (archaeology); Predictive modelling; Prostate cancer; Regression; Machine learning; Artificial intelligence; Computer science; Oncology; Statistics; Internal medicine; Cancer","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":[0.003027132,0.001011501,0.002261704,0.002487269,0.0001777367,0.001297142,0.001382984,0.000868513,0.00255793],"category_scores_gemma":[0.01427842,0.0003152562,0.001952155,0.002750686,0.0003284743,0.001228763,0.0004244685,0.001309725,0.0005743894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135815,"about_ca_system_score_gemma":0.002564038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004040458,"about_ca_topic_score_gemma":0.004968632,"domain_scores_codex":[0.9984951,0.0006831222,0.0002181625,0.000150841,0.0004082534,0.00004444252],"domain_scores_gemma":[0.9947413,0.004077013,0.0006279683,0.00007622146,0.0004282572,0.00004925707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002988393,0.00008367367,0.003598128,0.05392614,0.001854864,0.0003096431,0.0001111982,0.00816387,0.0001932402,0.003814848,0.02006884,0.9075766],"study_design_scores_gemma":[0.000461833,0.001061389,0.04062562,0.2294837,0.01353968,0.005653135,0.0007209943,0.02628611,0.003176686,0.03848478,0.6401149,0.0003910949],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005940456,0.9962716,0.001202648,0.0007337516,0.000190929,0.00002430477,0.0001327567,0.00001810104,0.0008317712],"genre_scores_gemma":[0.01606639,0.9808307,0.002139337,0.0002079972,0.0002075294,0.00004476732,0.0002365645,0.000004832252,0.0002619867],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004040458,"threshold_uncertainty_score":0.01600915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216396055258347,"score_gpt":0.3040177199100612,"score_spread":0.2818537593574777,"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."}}