{"id":"W4387930839","doi":"10.1089/bio.2022.0190","title":"Biospecimen Qualification in a Clinical Biobank of Urological Diseases","year":2023,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Biobank; Biomarker discovery; Biorepository; Workflow; Context (archaeology); Biomarker; Medicine; Medical physics; Computer science; Bioinformatics; Biology; Database","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003856782,0.0001163482,0.0004381161,0.0001727675,0.00004483221,0.0000241532,0.0001812216,0.0001969681,0.0001318532],"category_scores_gemma":[0.03915519,0.00009262186,0.0000898742,0.0006798888,0.0002340203,0.00007430326,0.0001417568,0.0001439752,0.00001929438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001305809,"about_ca_system_score_gemma":0.00002245615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000172038,"about_ca_topic_score_gemma":0.000004949856,"domain_scores_codex":[0.9972755,0.0006561292,0.001245601,0.0003460527,0.0002764082,0.0002003395],"domain_scores_gemma":[0.9861387,0.01308573,0.0003272024,0.0002861318,0.00008475733,0.00007745544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002215726,0.0003465523,0.6121364,0.0001647037,0.00003172749,0.000007404158,0.00009847204,0.000001040807,0.00181555,0.3493162,0.001987675,0.03387267],"study_design_scores_gemma":[0.0005299766,0.0000818544,0.5012691,0.00004338968,0.00001848344,3.178772e-7,0.00004199821,0.0009535847,0.0002218939,0.4963059,0.0004471256,0.00008631599],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937538,0.00006985664,0.002949932,0.001936409,0.0002969319,0.0003989017,0.00007540216,0.0001622397,0.0003565424],"genre_scores_gemma":[0.9369515,0.0002396963,0.06234841,0.0001722704,0.0001742193,0.0000262538,0.0000158755,0.00001409185,0.00005773695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1469897,"threshold_uncertainty_score":0.9689384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7818091384601079,"score_gpt":0.6197198261396243,"score_spread":0.1620893123204836,"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."}}