{"id":"W4390372773","doi":"10.1016/j.ijbiomac.2023.129071","title":"Poly (vinyl alcohol)-gelatin-sericin copolymerized film fortified with vesicle-entrapped demethoxycurcumin/bisdemethoxycurcumin for improved stability, antibacterial, anti-inflammatory, and skin tissue regeneration","year":2023,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Wound Healing and Treatments","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Center of Excellence for Innovation in Chemistry; Ministry of Higher Education, Science, Research and Innovation, Thailand; Chiang Mai University; Thailand Science Research and Innovation; Canadian Mennonite University","keywords":"Chemistry; Vinyl alcohol; Gelatin; Vesicle; Sericin; Biocompatibility; Zeta potential; Materials science; Biochemistry; Organic chemistry; Polymer; Nanotechnology; Membrane; Nanoparticle","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001156935,0.0002855449,0.0001725492,0.0001584963,0.0001042422,0.000195969,0.0001493043,0.0002615514,0.0006637941],"category_scores_gemma":[0.00009371408,0.0001316942,0.0001703037,0.0001152447,0.0001652894,0.0002737065,0.0001157488,0.0002899087,0.0001324483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001831883,"about_ca_system_score_gemma":0.0001657043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000647125,"about_ca_topic_score_gemma":0.001076793,"domain_scores_codex":[0.9999373,0.00000669499,0.000005511788,0.00002037798,0.00001137197,0.00001882384],"domain_scores_gemma":[0.9999273,0.00001211042,0.00002309871,0.000005915849,0.00001038362,0.00002114883],"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":[0.00003020022,0.000005362727,0.00001471574,0.00001331115,0.000001464808,0.00001373949,0.000002749372,0.00001926005,0.9996167,0.00002096971,0.000003887628,0.0002576699],"study_design_scores_gemma":[0.000003487235,0.00008693437,0.0005533181,0.000002164059,0.00000940445,0.00003792774,0.000003885256,0.0002803898,0.9986972,0.000004519501,0.0003188208,0.000001961472],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951537,0.001213596,0.002659929,0.00003460695,0.0000370817,0.00001427757,0.00005447793,0.00007718502,0.0007550756],"genre_scores_gemma":[0.996291,0.0004162455,0.002029839,0.00001747999,0.000006448159,0.000007423385,0.00004692467,0.00001989619,0.001164748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006637941,"threshold_uncertainty_score":0.002220571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04583766075255101,"score_gpt":0.3370810560641435,"score_spread":0.2912433953115924,"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."}}