{"id":"W4396927173","doi":"10.3390/microorganisms12050966","title":"Metallo-Glycodendrimeric Materials against Enterotoxigenic Escherichia coli","year":2024,"lang":"en","type":"article","venue":"Microorganisms","topic":"Dendrimers and Hyperbranched Polymers","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Université de Montréal","keywords":"Chemistry; Dendrimer; Bacteria; Escherichia coli; Minimum inhibitory concentration; Enterotoxigenic Escherichia coli; Microbiology; Biofilm; Nuclear chemistry; Biochemistry; In vitro; Biology","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":[0.00009916171,0.0003862578,0.0001285495,0.0001667844,0.00007349302,0.0001146985,0.0001345172,0.000263279,0.000425225],"category_scores_gemma":[0.0001224202,0.00008772641,0.0001651405,0.00008473166,0.00008825872,0.00008649057,0.0001214108,0.0001980278,0.0001454974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244045,"about_ca_system_score_gemma":0.00008495318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002154562,"about_ca_topic_score_gemma":0.0004530054,"domain_scores_codex":[0.9999236,0.00001322254,0.000007046408,0.00001304892,0.00002441754,0.00001863881],"domain_scores_gemma":[0.9999421,0.000009294789,0.00001961206,0.000005796971,0.00001242968,0.00001081564],"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":[0.00003571016,0.0000123046,0.00004156246,0.00002629133,0.000001744605,0.00001518798,0.000003484897,0.00004010429,0.9990716,0.000009933346,0.0000126929,0.000729259],"study_design_scores_gemma":[0.000006453069,0.0005878848,0.001261774,0.000003462413,0.0000100803,0.00008706892,0.000005584527,0.0001892551,0.9972028,0.00000554663,0.0006384556,0.000001713027],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961159,0.001174747,0.001416652,0.0000414754,0.00002031893,0.00002555296,0.00007436736,0.00004248817,0.001088553],"genre_scores_gemma":[0.9956658,0.0005985291,0.002002922,0.0000341926,0.000008567224,0.00001945159,0.0001446366,0.000006604169,0.001519428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000425225,"threshold_uncertainty_score":0.001422524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009065424414290849,"score_gpt":0.2290315448639678,"score_spread":0.219966120449677,"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."}}