{"id":"W2972920778","doi":"10.1089/ten.tec.2019.0121","title":"Dynamic Bioreactors with Integrated Microfabricated Devices for Mechanobiological Screening","year":2019,"lang":"en","type":"article","venue":"Tissue Engineering Part C Methods","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Ted Rogers Centre for Heart Research; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Mechanobiology; Tissue engineering; Bioreactor; Biomaterial; Biomedical engineering; Materials science; Microscale chemistry; Context (archaeology); Self-healing hydrogels; Nanotechnology; Chemistry; Cell biology; Engineering; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001208229,0.0003286954,0.0004356249,0.0002447843,0.00004056689,0.00005530992,0.0003930113,0.0002347532,0.0002246132],"category_scores_gemma":[0.0003980171,0.0002590608,0.00006679149,0.0006519209,0.00004417083,0.00008467319,0.0000689764,0.0004524947,0.00007176609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009059595,"about_ca_system_score_gemma":0.00002216479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001048242,"about_ca_topic_score_gemma":0.000001298974,"domain_scores_codex":[0.9983139,0.00008234353,0.0003270092,0.0003930457,0.0002001318,0.0006835639],"domain_scores_gemma":[0.9983435,0.0009620557,0.00003931566,0.0003656795,0.0000824206,0.0002070102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003735301,0.00002079672,0.0004215276,0.0004171768,0.0002163506,0.00000666099,0.00006965736,0.0331544,0.8900119,0.0001849319,0.0002694524,0.07518977],"study_design_scores_gemma":[0.0004976056,0.0002320451,0.001425665,0.0002402049,0.00003073774,0.00001798384,0.00003681228,0.5024034,0.2196154,0.00001917925,0.2749322,0.0005486938],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1795322,0.0004214673,0.8177727,0.00004984794,0.0004952166,0.0005479093,0.00001896215,0.0009913715,0.0001703217],"genre_scores_gemma":[0.2742582,0.00002148161,0.7250206,0.00001239355,0.0000493103,0.00009059021,0.00008183304,0.0001013309,0.0003642974],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6703966,"threshold_uncertainty_score":0.9999862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521912200888468,"score_gpt":0.3388274705971507,"score_spread":0.313608348588266,"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."}}