{"id":"W2055508382","doi":"10.1089/bio.2011.9403","title":"What Are the Most Oppressing Legal and Ethical Issues Facing Biorepositories and What Are Some Strategies to Address Them?","year":2011,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Cancer Institute","keywords":"Biobank; Ethical issues; Sociology; Library science; Law; Engineering ethics; Political science; Computer science; Engineering; Biology; Bioinformatics","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.1451494,0.00233641,0.003235543,0.004248771,0.01814561,0.04158038,0.007917057,0.03411053,0.01265002],"category_scores_gemma":[0.2720395,0.001704672,0.002586799,0.003797393,0.04283617,0.03812202,0.01111367,0.029699,0.004732545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01201816,"about_ca_system_score_gemma":0.0701903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01432975,"about_ca_topic_score_gemma":0.03619933,"domain_scores_codex":[0.9204067,0.04700785,0.005077241,0.004128477,0.01668847,0.00669121],"domain_scores_gemma":[0.6433754,0.2207418,0.02893747,0.01187552,0.06143507,0.03363476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001159916,0.0004039741,0.00568844,0.003063426,0.0002526855,0.002172294,0.007974326,0.0009584721,0.0006905413,0.3421569,0.408302,0.2282209],"study_design_scores_gemma":[0.0001119103,0.0001856842,0.004499467,0.01617029,0.0002316793,0.003765184,0.03944489,0.002153524,0.0007972628,0.4377565,0.4943376,0.0005460086],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001500939,0.027007,0.01155781,0.9446148,0.006118333,0.000187889,0.0000827949,0.0001906737,0.008739844],"genre_scores_gemma":[0.09059716,0.1273639,0.1265608,0.6014853,0.03061399,0.002499487,0.0004083516,0.0005061129,0.01996495],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9658895,"threshold_uncertainty_score":0.7676328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08805131490944336,"score_gpt":0.3262185566777444,"score_spread":0.2381672417683011,"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."}}