{"id":"W4366992310","doi":"10.1016/j.tig.2023.04.001","title":"Biobanking and research quality: think locally, act globally","year":2023,"lang":"en","type":"article","venue":"Trends in Genetics","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Biobank; Biology; Corporate governance; Quality (philosophy); Data science; Engineering ethics; Bioinformatics; Business; Computer science; Engineering","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01407027,0.0001313005,0.000311515,0.0007382878,0.0001141953,0.00007419748,0.0003733755,0.0004725169,0.0001574798],"category_scores_gemma":[0.007501455,0.000118542,0.00006216462,0.002466887,0.0006316105,0.0000256623,0.0007827275,0.002354926,0.0001665901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001292888,"about_ca_system_score_gemma":0.0003508444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001553508,"about_ca_topic_score_gemma":0.001126094,"domain_scores_codex":[0.9955972,0.0003955328,0.0005422427,0.0005371188,0.002191528,0.000736321],"domain_scores_gemma":[0.9930712,0.005492682,0.00004133672,0.0007468209,0.0003808932,0.0002670553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003492694,0.0002585591,0.2654743,0.0004680467,0.00007773846,0.0005080952,0.002072651,0.00005290654,0.002590386,0.02471237,0.006554703,0.696881],"study_design_scores_gemma":[0.001992479,0.0006980455,0.8733474,0.0004414127,0.00001870174,0.00001715339,0.0006903925,0.001894689,0.0009944268,0.1097365,0.009931948,0.0002368672],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9412727,0.001113757,0.00001959967,0.01779698,0.0001579261,0.0001930177,0.00001120526,0.0001290275,0.03930573],"genre_scores_gemma":[0.979192,0.005133723,0.002598603,0.0004603246,0.0002152721,0.00001190216,0.00002570499,0.00003762047,0.01232481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6966441,"threshold_uncertainty_score":0.9999467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7627135662500916,"score_gpt":0.6852536027037879,"score_spread":0.07745996354630369,"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."}}