{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000799144,0.0002630446,0.000573897,0.0002184242,0.0001384306,0.00009885883,0.0001896628,0.0001821672,0.00004216333],"category_scores_gemma":[0.0004487133,0.0001753676,0.0001602564,0.0001804618,0.0001642544,0.0001468652,0.00006566559,0.0001921254,0.000004331342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007461925,"about_ca_system_score_gemma":0.0001492279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000244722,"about_ca_topic_score_gemma":0.000007301188,"domain_scores_codex":[0.997981,0.0001726912,0.0008398636,0.0003496429,0.0003294539,0.0003273974],"domain_scores_gemma":[0.9983107,0.0003430183,0.0005599013,0.0001570098,0.0004249158,0.0002044087],"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":[0.002831723,0.0002404792,0.01109522,0.00003801346,0.0005542963,0.0001656082,0.0001986348,0.000002425976,0.9482047,0.0002216593,0.0001072738,0.03634],"study_design_scores_gemma":[0.00915879,0.003264787,0.0823834,0.00024143,0.0002433831,0.0006671466,0.0004296373,0.00133641,0.8993074,0.001109304,0.001530069,0.0003282951],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796471,0.0004116085,0.01530343,0.00341141,0.000462736,0.0005451564,0.000116332,0.00006103011,0.00004117724],"genre_scores_gemma":[0.9776486,0.0002491986,0.02113599,0.0002226783,0.0004044597,0.0000261729,0.0002334332,0.00002855546,0.00005091606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07128818,"threshold_uncertainty_score":0.7151282,"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."}}