{"id":"W2017635465","doi":"10.1002/bit.23202","title":"Flow dynamics within a bioreactor for tissue engineering by residence time distribution analysis combined with fluorescence and magnetic resonance imaging to investigate forced permeability and apparent diffusion coefficient in a perfusion cell culture chamber","year":2011,"lang":"en","type":"article","venue":"Biotechnology and Bioengineering","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health and Social Services Centre University Institute of Geriatrics of Sherbrooke; Université de Sherbrooke","funders":"","keywords":"Residence time distribution; Bioreactor; Permeability (electromagnetism); Chemistry; Volumetric flow rate; Nuclear magnetic resonance; Materials science; Biomedical engineering; Analytical Chemistry (journal); Chromatography; Flow (mathematics); Mechanics; Physics","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":[0.0004264716,0.0004361469,0.0004075415,0.0002889892,0.000171583,0.0003796744,0.0002766763,0.0004307962,0.0004074362],"category_scores_gemma":[0.0003270152,0.0001266272,0.0002890297,0.0001825362,0.0002487245,0.0004628071,0.0001939975,0.0005155427,0.0001577827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005440986,"about_ca_system_score_gemma":0.0003466415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001017275,"about_ca_topic_score_gemma":0.0009095802,"domain_scores_codex":[0.9998469,0.00002084983,0.00001022167,0.00005702048,0.00004428119,0.00002058199],"domain_scores_gemma":[0.9997213,0.0001232331,0.00007243679,0.0000142212,0.0000467403,0.00002197001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001620974,0.00000680329,0.00009266157,0.00001461272,0.000001009192,0.000008515134,0.000008190853,0.0002553744,0.9981682,0.00003568771,0.000006649052,0.001386216],"study_design_scores_gemma":[0.000003858601,0.0001691149,0.00166291,0.000003859153,0.00001087195,0.00009238617,0.00001251229,0.01631702,0.9810104,0.00005348299,0.0006547004,0.000008828948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8242217,0.002130206,0.1720778,0.000170253,0.00004278893,0.00006506054,0.0002201662,0.0003865827,0.0006855053],"genre_scores_gemma":[0.901629,0.001499102,0.09499782,0.00007980708,0.0000285213,0.0001344555,0.0002250844,0.00006043743,0.001345854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001017275,"threshold_uncertainty_score":0.003947735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004941180519504952,"score_gpt":0.1948840515424733,"score_spread":0.1899428710229684,"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."}}