{"id":"W4254213139","doi":"10.1089/bio.2013.0042","title":"Defining Biobank","year":2013,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biobank; Sample (material); Population; Confusion; Data science; Psychology; Medicine; Computer science; Biology; Bioinformatics; Environmental health","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":[],"consensus_categories":[],"category_scores_codex":[0.0008371509,0.00008445878,0.0001378559,0.00009917792,0.0001193424,0.00009760222,0.00008954132,0.0002164655,0.0007321797],"category_scores_gemma":[0.002464038,0.00006626319,0.00004086645,0.0002008404,0.0001315013,0.0001656737,0.0001358223,0.0004617268,0.0003254285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002362497,"about_ca_system_score_gemma":0.00007120004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003003547,"about_ca_topic_score_gemma":0.0000266552,"domain_scores_codex":[0.9988101,0.00002504056,0.0002650864,0.0002466562,0.0004355415,0.0002175503],"domain_scores_gemma":[0.9985119,0.000720082,0.00005412802,0.0002428649,0.0003344003,0.0001366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005240498,0.0001009907,0.7443796,0.0003118068,0.00004408708,0.000009371784,0.0001991337,3.966652e-7,0.03848833,0.16418,0.004183944,0.04804985],"study_design_scores_gemma":[0.001087959,0.0002564022,0.9185669,0.0003609844,0.00002358841,0.00002277959,0.0002217367,0.001960969,0.006523488,0.05528827,0.01547971,0.0002072344],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660625,0.0006229135,0.0002115986,0.01652956,0.0001056742,0.0003248911,0.000001898019,0.0001017812,0.01603913],"genre_scores_gemma":[0.9891143,0.0003553572,0.005530283,0.002463047,0.0001023729,0.00002308363,0.00001832817,0.00001254127,0.002380719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1741872,"threshold_uncertainty_score":0.8016855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3354106859810756,"score_gpt":0.5036578154055444,"score_spread":0.1682471294244688,"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."}}