{"id":"W3002407685","doi":"10.1021/acsami.9b21066","title":"Fabrication and Characterization of Drug-Loaded Conductive Poly(glycerol sebacate)/Nanoparticle-Based Composite Patch for Myocardial Infarction Applications","year":2020,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Electrospun Nanofibers in Biomedical Applications","field":"Materials Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"H2020 European Research Council; Terveyden Tutkimuksen Toimikunta; Sigrid Juséliuksen Säätiö; Tekes","keywords":"Materials science; Biomaterial; Elastomer; Electrical conductor; Composite number; Polypyrrole; Biomedical engineering; Drug delivery; Conductive polymer; Degradation (telecommunications); Biocompatibility; Composite material; Nanotechnology; Polymer; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003028849,0.0002565603,0.0004479188,0.00007640157,0.000202893,0.00009969925,0.0003214296,0.0001373737,0.00009288971],"category_scores_gemma":[0.00002070792,0.0002508826,0.00002367602,0.00030696,0.0003310527,0.0002008984,0.0001100562,0.00007182753,0.0000580408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005696299,"about_ca_system_score_gemma":0.0000646382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003776195,"about_ca_topic_score_gemma":0.000001380516,"domain_scores_codex":[0.9980419,0.00007554922,0.0007034061,0.0006033204,0.0002595825,0.0003162893],"domain_scores_gemma":[0.9986523,0.0001424011,0.0005465155,0.000298782,0.0002348903,0.0001251237],"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":[0.0004331664,0.00008883853,0.00006150798,0.0001467489,0.00002941073,4.072525e-8,0.0005080797,0.000004876342,0.9961288,0.001288838,0.00009126871,0.001218455],"study_design_scores_gemma":[0.0008760297,0.0001262781,0.000728263,0.00001752827,0.00009302866,9.71441e-7,0.00008770297,0.00003020803,0.9963894,0.000812817,0.0005976435,0.000240162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689772,0.00006273262,0.02551461,0.002365725,0.0001497184,0.002100287,0.000625334,0.0001740603,0.00003035574],"genre_scores_gemma":[0.9913801,0.0000286112,0.005023189,0.000638279,0.000200643,0.002182194,0.0004967041,0.00003965526,0.00001064622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0224029,"threshold_uncertainty_score":0.9999943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01281387795716379,"score_gpt":0.2406036851106444,"score_spread":0.2277898071534807,"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."}}