{"id":"W2038172553","doi":"10.1038/nprot.2008.40","title":"Cardiac tissue engineering using perfusion bioreactor systems","year":2008,"lang":"en","type":"article","venue":"Nature Protocols","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":272,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Heart, Lung, and Blood Institute; National Institutes of Health","keywords":"Tissue engineering; Bioreactor; Biomedical engineering; Cell culture; Perfusion; Scaffold; Materials science; Biochemical engineering; Chemistry; Cell biology; Biology; Medicine; Cardiology; Engineering","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":[0.0001527334,0.0002323908,0.0004634418,0.0001641805,0.00009476823,0.00001210551,0.00007422108,0.0003714644,0.00002244819],"category_scores_gemma":[0.000141519,0.0001698662,0.00007730474,0.0002804765,0.00003930541,0.00005359587,0.00002659295,0.0007657575,0.00001813936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001196567,"about_ca_system_score_gemma":0.00008773934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002601078,"about_ca_topic_score_gemma":9.635779e-8,"domain_scores_codex":[0.9988018,0.00002567988,0.0002288036,0.0002696869,0.0003903775,0.0002836506],"domain_scores_gemma":[0.9992763,0.00003020776,0.00005254571,0.000308703,0.0001358582,0.0001964116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004408045,0.00006460013,0.003239592,0.0004840534,0.00005090572,0.0002361608,0.0002312353,0.0008677376,0.9923867,0.000282306,0.001601591,0.0005110459],"study_design_scores_gemma":[0.001804958,0.0005599447,0.008069946,0.001982926,0.00007681087,0.001063454,0.00003606699,0.008174608,0.2625394,5.758833e-7,0.7152681,0.0004231702],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8056421,0.02727952,0.01029212,0.0005167469,0.003435923,0.1510801,0.00003695042,0.001078359,0.0006382483],"genre_scores_gemma":[0.9575979,0.00003368318,0.01061401,0.00003876691,0.004335391,0.02086088,0.00004028778,0.0001217586,0.006357391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7298473,"threshold_uncertainty_score":0.6926943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02730336249502219,"score_gpt":0.3234197392152813,"score_spread":0.2961163767202591,"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."}}