{"id":"W2344600570","doi":"10.1021/acsbiomaterials.5b00525","title":"Highly Elastic and Moldable Polyester Biomaterial for Cardiac Tissue Engineering Applications","year":2016,"lang":"en","type":"article","venue":"ACS Biomaterials Science & Engineering","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Prepolymer; Biomaterial; Elastomer; Materials science; Polyester; Tissue engineering; Polymer; Elastic modulus; Self-healing hydrogels; Ultimate tensile strength; Composite material; Monomer; Biomedical engineering; Polymer chemistry; Nanotechnology; Polyurethane","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002322861,0.0005184967,0.0001336031,0.0003343793,0.0001378016,0.0002690399,0.0001575964,0.0005134864,0.00174934],"category_scores_gemma":[0.0002324655,0.0002319419,0.0002708113,0.0001880269,0.0001504119,0.000384869,0.0001757317,0.0004357186,0.001007944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001241897,"about_ca_system_score_gemma":0.0001441455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006423006,"about_ca_topic_score_gemma":0.0001945356,"domain_scores_codex":[0.9998803,0.0000135618,0.00001277186,0.00002130155,0.0000570083,0.00001507073],"domain_scores_gemma":[0.9998728,0.00002528551,0.00004963412,0.00001593895,0.00001647189,0.00001997957],"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":[0.00001047337,0.00001735776,0.00007091079,0.00005710899,0.000002211517,0.00006393104,0.000006256379,0.0001921143,0.9937557,0.0002177484,0.00005661514,0.005549602],"study_design_scores_gemma":[0.000009917355,0.0001689568,0.001282302,0.00001579339,0.00001198515,0.0006696852,0.000009343213,0.00106056,0.9853087,0.0001581708,0.0112929,0.00001176049],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7431046,0.03447411,0.1939188,0.0006740061,0.0006922787,0.0004629801,0.0008823898,0.0009856593,0.02480511],"genre_scores_gemma":[0.8346084,0.01006684,0.1364513,0.0004116682,0.0001475725,0.0002105132,0.0005761277,0.0001172218,0.01741042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00174934,"threshold_uncertainty_score":0.005852103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008741739923398524,"score_gpt":0.249403977220183,"score_spread":0.2406622372967845,"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."}}