{"id":"W2113859811","doi":"10.1177/1747016113488858","title":"Public deliberation to develop ethical norms and inform policy for biobanks: Lessons learnt and challenges remaining","year":2013,"lang":"en","type":"article","venue":"Research Ethics","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Guelph","funders":"","keywords":"Deliberation; Biobank; Political science; Corporate governance; Engineering ethics; Public relations; Public engagement; Public policy; Law; Politics; Engineering; Management; Economics; Bioinformatics; Biology","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","research_integrity"],"consensus_categories":["metaresearch","research_integrity"],"category_scores_codex":[0.0429142,0.0001845277,0.0003724987,0.0007818743,0.0007598187,0.0004086702,0.0002954608,0.002544,0.00004007762],"category_scores_gemma":[0.4589949,0.000149067,0.00004313859,0.001074491,0.001233913,0.0002686939,0.0009107715,0.01468096,0.00009741532],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002717043,"about_ca_system_score_gemma":0.006417989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005057279,"about_ca_topic_score_gemma":0.003003631,"domain_scores_codex":[0.9941716,0.0005019914,0.0005680016,0.0006692477,0.002945454,0.001143714],"domain_scores_gemma":[0.8701932,0.1047244,0.0001114548,0.001156841,0.02128402,0.002530056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001278447,0.00006400007,0.0003667844,0.001991461,0.00005077658,0.000005787857,0.008933431,5.40025e-7,0.001420735,0.8369025,0.0005963588,0.1495398],"study_design_scores_gemma":[0.003156052,0.00426025,0.08085483,0.00217078,0.0000223175,0.00009254221,0.00978214,0.001770678,0.001331257,0.7923913,0.1035227,0.0006451688],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05801972,0.001158419,0.0008086974,0.9319068,0.00003993198,0.001702595,0.000007949297,0.00006711648,0.006288785],"genre_scores_gemma":[0.9177617,0.05296198,0.01755933,0.00747234,0.00061329,0.0006384289,0.00002708742,0.00007273795,0.002893086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9244344,"threshold_uncertainty_score":0.9992147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9344429354460383,"score_gpt":0.691832575104417,"score_spread":0.2426103603416213,"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."}}