{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002817591,0.0006232065,0.0003147013,0.0002151717,0.00009649333,0.0002784435,0.000168999,0.0003426807,0.0003645555],"category_scores_gemma":[0.0003622178,0.0001759308,0.0002148437,0.0002567799,0.0001680033,0.0003442777,0.0002007253,0.0003547574,0.0001955484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000175699,"about_ca_system_score_gemma":0.0001019203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007606076,"about_ca_topic_score_gemma":0.0001682772,"domain_scores_codex":[0.9997686,0.00005439608,0.00002833644,0.00006015381,0.00005866544,0.0000299546],"domain_scores_gemma":[0.9997359,0.00006651742,0.00009662548,0.00002183285,0.00003593448,0.00004308964],"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":[0.00002969212,0.00001285219,0.00007063349,0.000022696,0.000004496047,0.00002214417,0.000004934068,0.00007487398,0.9985499,0.00001091638,0.000004069148,0.001192815],"study_design_scores_gemma":[0.000005529961,0.0003122197,0.0007672431,0.000002202971,0.0000132762,0.0001222825,0.00000224572,0.0003034978,0.9979686,0.00000608403,0.0004939178,0.000002902128],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925402,0.001784551,0.004981278,0.00003323939,0.00001048265,0.00003266488,0.00003787669,0.00004397755,0.0005357411],"genre_scores_gemma":[0.9871882,0.001028734,0.0108564,0.00004839351,0.00001513118,0.0000475112,0.0001121456,0.00003080379,0.0006727057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006232065,"threshold_uncertainty_score":0.001490116,"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."}}