{"id":"W3108890320","doi":"10.1089/bio.2020.0083","title":"Biobanking in the COVID-19 Era and Beyond: Part 2. A Set of Tool Implementation Case Studies","year":2020,"lang":"en","type":"article","venue":"Biopreservation and Biobanking","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; CancerCare Manitoba; Ontario Institute for Cancer Research","funders":"National Cancer Institute; World Health Organization","keywords":"Biobank; Task (project management); Set (abstract data type); Task force; Coronavirus disease 2019 (COVID-19); Data science; Best practice; Computer science; Work (physics); Adaptability; Knowledge management; Engineering; Medicine; Political science; Bioinformatics; Systems engineering; Management; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05285701,0.0007835732,0.0008765152,0.003200458,0.007491808,0.01091812,0.003792929,0.006372453,0.002464188],"category_scores_gemma":[0.05220464,0.000908323,0.0009731423,0.005321523,0.007136431,0.008968223,0.009528932,0.005339056,0.0005400162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01227542,"about_ca_system_score_gemma":0.008454837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01037098,"about_ca_topic_score_gemma":0.01736518,"domain_scores_codex":[0.9300702,0.05594012,0.002505526,0.001759414,0.005573481,0.004151351],"domain_scores_gemma":[0.9357395,0.0466894,0.004161583,0.004791892,0.00516499,0.003452753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007439365,0.007392236,0.08240149,0.002597236,0.0001393617,0.02663269,0.4846075,0.009190525,0.006841818,0.1243493,0.0170567,0.2380472],"study_design_scores_gemma":[0.0003514139,0.002818173,0.03402467,0.004075902,0.0001336151,0.009283679,0.6098823,0.01039541,0.01261313,0.02707298,0.2890106,0.0003381531],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8719722,0.002382016,0.0480344,0.0140093,0.0002543659,0.005462728,0.0004075491,0.0001842653,0.05729322],"genre_scores_gemma":[0.8706828,0.003329769,0.1025725,0.003992829,0.00009716817,0.005529542,0.0004329994,0.0001592618,0.01320318],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05285701,"threshold_uncertainty_score":0.2795379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6889840094913504,"score_gpt":0.6030613568899987,"score_spread":0.08592265260135168,"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."}}