{"id":"W2760817034","doi":"10.1021/acsami.7b09471","title":"Antimicrobial Peptide–Polymer Conjugates with High Activity: Influence of Polymer Molecular Weight and Peptide Sequence on Antimicrobial Activity, Proteolysis, and Biocompatibility","year":2017,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Antimicrobial Peptides and Activities","field":"Immunology and Microbiology","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Peptide; Antimicrobial; Materials science; Biocompatibility; Proteolysis; Polymer; Conjugate; Antimicrobial peptides; Nanotechnology; Biochemistry; Organic chemistry; Chemistry; Enzyme","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","sts"],"consensus_categories":[],"category_scores_codex":[0.0002898156,0.0006365429,0.001094136,0.0001421334,0.0006376858,0.0003222481,0.0005328011,0.0003542338,0.00009666785],"category_scores_gemma":[0.00003182342,0.0005161141,0.00003822264,0.00005888157,0.002726349,0.0005469758,0.0006680816,0.0003309584,0.00003481803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000310504,"about_ca_system_score_gemma":0.00007619315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003394209,"about_ca_topic_score_gemma":0.00009213654,"domain_scores_codex":[0.9977192,0.0001665856,0.000461879,0.0009588815,0.00009543468,0.0005979624],"domain_scores_gemma":[0.9979858,0.0001218016,0.0008881381,0.0008588123,0.00009471194,0.00005074358],"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":[0.002405441,0.0002527229,0.0009335656,0.0002652757,0.0003535762,0.00001046297,0.000291856,0.000009677946,0.9939231,0.0006186097,0.0001193887,0.0008163048],"study_design_scores_gemma":[0.001554184,0.0003840731,0.006037338,0.0003865994,0.00014683,0.00007004394,0.00005002478,1.309681e-7,0.9907059,0.0000668623,0.00001666511,0.0005813707],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975331,0.0001368056,0.000009982678,0.0004977771,0.00019193,0.0008626296,0.000522363,0.00007349807,0.0001718974],"genre_scores_gemma":[0.9991136,0.0001650807,0.00009933711,0.0001812595,0.0000410912,0.00004856572,0.00003170736,0.00005803913,0.0002612731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005103773,"threshold_uncertainty_score":0.9999877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01050389029272056,"score_gpt":0.2348689420803687,"score_spread":0.2243650517876481,"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."}}