{"id":"W3173920669","doi":"10.1016/j.euf.2021.06.002","title":"Biorepositories and Databanks for the Development of Novel Biomarkers for Genitourinary Cancer Prevention and Management","year":2021,"lang":"en","type":"review","venue":"European Urology Focus","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Princess Margaret Cancer Centre; University Health Network","funders":"Princess Margaret Cancer Foundation","keywords":"Biorepository; Biobank; Translational research; Medicine; Biomarker discovery; Context (archaeology); Best practice; Informed consent; Data science; Medical physics; Bioinformatics; Pathology; Alternative medicine; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003183823,0.0002104094,0.0007353705,0.0001037561,0.0001690385,0.00001958767,0.0002174868,0.0001941276,0.000006194801],"category_scores_gemma":[0.001027672,0.0001388532,0.0001722676,0.0001092489,0.0003654981,0.00001876397,0.0006215442,0.0004672743,7.77743e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003410279,"about_ca_system_score_gemma":0.0003765658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003239028,"about_ca_topic_score_gemma":0.00003150889,"domain_scores_codex":[0.9981132,0.0002028821,0.0007091278,0.0005289282,0.0002119526,0.0002339546],"domain_scores_gemma":[0.9946294,0.00439665,0.0002786998,0.0004297502,0.0001888844,0.00007654541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001372271,0.0001060418,0.00002733813,0.02412057,0.001869028,0.00002166409,0.00007930391,4.576654e-8,0.000005061461,0.001188342,0.000519765,0.9719256],"study_design_scores_gemma":[0.0009651784,0.000376866,0.0003091249,0.003620613,0.002250748,0.00005111655,0.00003287691,0.000005522036,0.000009373138,0.00007779005,0.9921756,0.0001251543],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003639023,0.9908274,0.005125668,0.0005520202,0.0003722309,0.002372694,0.00008949422,0.00001164184,0.0006124711],"genre_scores_gemma":[0.00003658271,0.9791865,0.0184772,0.00004255565,0.0002643041,0.0004051195,0.00009448957,0.00005808015,0.001435203],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9916559,"threshold_uncertainty_score":0.566227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4509923771034909,"score_gpt":0.5522435925953875,"score_spread":0.1012512154918966,"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."}}