{"id":"W4379375024","doi":"10.20944/preprints202306.0308.v1","title":"Antibacterial Thermo-Sensitive Silver Hydrogel Nanocomposite Improves Wound Healing","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Wound Healing and Treatments","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; California HIV/AIDS Research Program","keywords":"Wound healing; Silver nanoparticle; In vivo; Nanocomposite; Antibacterial activity; Scaffold; Self-healing hydrogels; Bacterial growth; In vitro; Materials science; Biomedical engineering; Nanoparticle; Chemistry; Bacteria; Medicine; Nanotechnology; Immunology; Biology; Biochemistry","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006853585,0.0007259676,0.00119503,0.0002928465,0.0002770276,0.00005791029,0.0003070063,0.0007408893,0.0001808901],"category_scores_gemma":[0.0001611107,0.0006784049,0.0005511141,0.0001908843,0.0001694668,0.0000765574,0.001380383,0.001362021,0.003708633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004710542,"about_ca_system_score_gemma":0.0005010524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002163148,"about_ca_topic_score_gemma":0.00003997689,"domain_scores_codex":[0.9959754,0.0001508697,0.0008420557,0.001657233,0.0005938413,0.0007806195],"domain_scores_gemma":[0.9970713,0.0001671437,0.0004382989,0.001673501,0.0002582596,0.0003915394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001349624,0.0008595058,0.4173813,0.001113641,0.002519091,0.0008839203,0.002847178,0.0001230436,0.5718354,0.0001057892,0.00009592189,0.0008855958],"study_design_scores_gemma":[0.003001026,0.0001546239,0.7855361,0.001747153,0.0009064323,0.0001295755,0.0001427405,0.0003452065,0.2045861,0.001430868,0.001228773,0.0007914404],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894115,0.0001182638,0.00001961934,0.0009888082,0.00258802,0.002007704,0.0001121985,0.0008218152,0.003932039],"genre_scores_gemma":[0.9908939,0.0002758088,0.0003073254,0.0003486047,0.001250912,0.0001715229,0.0006494781,0.0001966593,0.00590576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3681548,"threshold_uncertainty_score":0.9995667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1102099832110046,"score_gpt":0.3646744098490836,"score_spread":0.2544644266380789,"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."}}