{"id":"W4396588999","doi":"10.1002/adfm.202315957","title":"Tuning the Topography of Non‐Wetting Surfaces to Reduce Short‐Term Microbial Contamination Within Hospitals","year":2024,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Nanomaterials and Printing Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Wetting; Dewetting; Materials science; Surface tension; Candida albicans; Contamination; Staphylococcus aureus; Adsorption; Pseudomonas aeruginosa; Nanotechnology; Biophysics; Microbiology; Composite material; Bacteria; Chemistry; Biology; Physics","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":[0.0001090691,0.0002334292,0.0001655787,0.0001238616,0.000106615,0.0002942625,0.0002371428,0.000241655,0.0009070781],"category_scores_gemma":[0.0004075695,0.0001602757,0.0001216403,0.0000977181,0.0001496202,0.0002459067,0.0002196677,0.0002149347,0.0002268927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001756008,"about_ca_system_score_gemma":0.0001252011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004364939,"about_ca_topic_score_gemma":0.001027824,"domain_scores_codex":[0.9998705,0.00001522428,0.00001081604,0.00002046359,0.00005306373,0.00002992345],"domain_scores_gemma":[0.9997088,0.00007864236,0.000101634,0.00003084205,0.00005287301,0.00002712155],"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":[0.00001425662,0.000012374,0.0001857422,0.00002016171,0.000001976303,0.00001297962,0.000005703515,0.0002438846,0.9982532,0.00001736249,0.00002585312,0.001206486],"study_design_scores_gemma":[0.000004704993,0.000233534,0.004330663,0.000002356681,0.000006464895,0.00004812182,0.0000277994,0.002505504,0.992316,0.00001936959,0.0005006465,0.000004695697],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937826,0.0003459706,0.00491981,0.00004530962,0.0000220043,0.00002245947,0.00005280415,0.00007794606,0.0007311815],"genre_scores_gemma":[0.9950998,0.0001748953,0.004183116,0.00004090093,0.000007207625,0.00001417835,0.00004142081,0.00001416027,0.0004243093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009070781,"threshold_uncertainty_score":0.003034413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008314667425625947,"score_gpt":0.2260307183061739,"score_spread":0.217716050880548,"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."}}