{"id":"W2121191797","doi":"10.1002/chem.200800700","title":"Glycomimetics and Glycodendrimers as High Affinity Microbial Anti‐adhesins","year":2008,"lang":"en","type":"article","venue":"Chemistry - A European Journal","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":250,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Centre National de la Recherche Scientifique; Fonds Québécois de la Recherche sur la Nature et les Technologies; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Glycoconjugate; Bacterial adhesin; Lectin; Chemistry; Adhesion; Glycoprotein; Oligosaccharide; Biofilm; Biochemistry; Microbiology; Virulence; Biology; Bacteria; Organic chemistry","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":[0.0001945343,0.0003095587,0.0002692311,0.0001656883,0.0001148257,0.0002973259,0.0003393562,0.0002970069,0.001159288],"category_scores_gemma":[0.0001434604,0.0001299894,0.0001492115,0.0001524662,0.000189862,0.0002419637,0.0002038405,0.0004914843,0.0005120682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002729961,"about_ca_system_score_gemma":0.0001392988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003375965,"about_ca_topic_score_gemma":0.0005338159,"domain_scores_codex":[0.9998826,0.00002537981,0.000008547306,0.00001678785,0.00004275157,0.00002386909],"domain_scores_gemma":[0.9999402,0.000009267581,0.00001323581,0.00000540563,0.000009838887,0.00002204976],"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":[0.0002051229,0.00007194642,0.00004863275,0.0001088547,0.000006541665,0.00008015164,0.00002215375,0.0003432178,0.9892615,0.001457478,0.0002566007,0.008137893],"study_design_scores_gemma":[0.0001687045,0.00155176,0.0006618286,0.00001481303,0.0000193316,0.0002611638,0.0000136296,0.001036346,0.9765592,0.0002758992,0.01942298,0.00001441997],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9367425,0.02654248,0.01814035,0.0006857516,0.0005426205,0.0002611815,0.0004565093,0.0003570063,0.0162717],"genre_scores_gemma":[0.9671968,0.009916762,0.01270037,0.0002895794,0.00009427016,0.00008327464,0.0003043537,0.00003522095,0.00937943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001159288,"threshold_uncertainty_score":0.003878176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451285630682767,"score_gpt":0.2329889386086238,"score_spread":0.2184760823017961,"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."}}