{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003579738,0.0003619597,0.0004268092,0.0001368765,0.0001805564,0.0006846256,0.0005099843,0.0001450097,0.01102773],"category_scores_gemma":[0.0000135035,0.0003211577,0.0001535863,0.0003633224,0.0001619549,0.0003281242,0.0001740745,0.0001577342,0.01095677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008922497,"about_ca_system_score_gemma":0.0001353188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008805416,"about_ca_topic_score_gemma":0.00001220724,"domain_scores_codex":[0.9978158,0.0001131281,0.0004608574,0.0006727741,0.0002955571,0.0006418736],"domain_scores_gemma":[0.9992171,0.00003872866,0.00007694426,0.0004571023,0.00003412339,0.0001759986],"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":[0.0000230126,0.00004425084,0.000007476875,0.00006996062,0.00005720374,0.0001000084,0.0005961414,0.000001682477,0.9942581,0.0004980032,0.003882366,0.0004617897],"study_design_scores_gemma":[0.0002147852,0.00006761358,0.00006284004,0.00004923213,0.00007646646,0.00003418371,0.00007799845,0.000008581788,0.9274772,0.00007845846,0.07149422,0.0003584622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858082,0.004454272,0.0005320931,0.0002273826,0.004431238,0.0003372241,0.0001349601,0.0005764751,0.003498142],"genre_scores_gemma":[0.99112,0.00008003502,0.001908169,0.0007947705,0.0003672574,0.00004854648,0.00004732595,0.0001207613,0.005513104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06761186,"threshold_uncertainty_score":0.9999241,"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."}}