{"id":"W2915341629","doi":"10.5539/mas.v13n3p101","title":"Fabrication of Xanthan gum: Gelatin (Xnt:Gel) Hybrid Composite Hydrogels for Evaluating Skin Wound Healing Efficacy","year":2019,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Wound Healing and Treatments","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bangladesh Council of Scientific and Industrial Research; Council of Scientific and Industrial Research, India","keywords":"Self-healing hydrogels; Gelatin; Swelling; Wound healing; Glutaraldehyde; Composite number; Materials science; Skin repair; Xanthan gum; Silica gel; Fourier transform infrared spectroscopy; Citric acid; Chemical engineering; Chromatography; Chemistry; Polymer chemistry; Composite material; Surgery; Food science; Medicine; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001136894,0.0001631018,0.0003613993,0.0001771295,0.0002930046,0.00004174327,0.0001912916,0.00004512028,0.00001409396],"category_scores_gemma":[0.00007527059,0.0001449408,0.00007708328,0.0003023892,0.0001804022,0.00008999541,0.00005650332,0.0001212935,0.00005329814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001968962,"about_ca_system_score_gemma":0.0002667315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004986837,"about_ca_topic_score_gemma":0.000001309419,"domain_scores_codex":[0.9978936,0.00001761164,0.0004136053,0.0005565544,0.0007044857,0.0004140945],"domain_scores_gemma":[0.9987262,0.0001932145,0.0002392681,0.0004809098,0.0002101383,0.0001502822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000227469,0.0003097524,0.004530296,0.0001590119,0.00002816105,0.000001076084,0.001204198,0.002440433,0.9581791,0.0008271753,0.00001053093,0.0320828],"study_design_scores_gemma":[0.005061178,0.000515548,0.01791582,0.000243737,0.0001424627,0.00002723738,0.0000918556,0.6733086,0.2976299,0.004706621,0.00008305188,0.0002739369],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508188,0.00007484436,0.04493744,0.0001344403,0.0001076264,0.001498981,0.00001080934,0.00005656619,0.002360492],"genre_scores_gemma":[0.9811984,0.000002461276,0.01826981,0.0001262674,0.00005312884,0.00006059089,0.00003768063,0.00002155788,0.0002301045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6708682,"threshold_uncertainty_score":0.5910513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04298015238800128,"score_gpt":0.3490611060735589,"score_spread":0.3060809536855576,"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."}}