{"id":"W3000472132","doi":"10.1016/j.msec.2020.110674","title":"Assessing the potential of boronic acid/chitosan/bioglass composite materials for tissue engineering applications","year":2020,"lang":"en","type":"article","venue":"Materials Science and Engineering C","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Allison University; Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation; Canada Foundation for Innovation","keywords":"Chitosan; Materials science; Composite number; Tissue engineering; Simulated body fluid; Boronic acid; Scanning electron microscope; Chemical engineering; Biomedical engineering; Nanotechnology; Composite material; Organic chemistry; Chemistry","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":[0.0007219092,0.0003319385,0.0004805145,0.0001393735,0.0001580492,0.0005439707,0.0005341823,0.00009964734,0.00002925776],"category_scores_gemma":[0.0001340566,0.0002968067,0.00003521209,0.0004504778,0.0001299523,0.0005463861,0.0001417163,0.00009084285,0.000008964873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006516573,"about_ca_system_score_gemma":0.00005307912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008203978,"about_ca_topic_score_gemma":1.157061e-7,"domain_scores_codex":[0.9981171,0.00001317018,0.000555335,0.0003576139,0.0003958034,0.0005610111],"domain_scores_gemma":[0.9992573,0.00006180345,0.00008181264,0.0003236815,0.0001014111,0.0001739728],"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":[0.000004312817,0.000005079692,9.784686e-7,0.0006478972,0.00002107707,0.000001236121,0.0001447924,0.06754214,0.9307044,0.0005254718,0.00004325066,0.0003593876],"study_design_scores_gemma":[0.000226722,0.00004020607,0.0006614309,0.000068735,0.00004062782,0.00001727047,0.00003278538,0.02475679,0.9717423,0.00001313093,0.002080675,0.0003193322],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8838793,0.0004604206,0.1125112,0.0002570346,0.001305239,0.0008051373,0.0001500992,0.0006062234,0.00002527869],"genre_scores_gemma":[0.9900123,0.00004296841,0.009077618,0.00002673299,0.0005152025,0.0002202394,0.00001702864,0.00008608902,0.000001820195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.106133,"threshold_uncertainty_score":0.9999484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009433966093613442,"score_gpt":0.2310967478061266,"score_spread":0.2216627817125132,"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."}}