{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003930318,0.0002320866,0.0001850464,0.00004105197,0.0004504514,0.00009882379,0.0003388553,0.00009394212,0.0003051615],"category_scores_gemma":[0.0002492368,0.0002257257,0.000119297,0.0001041155,0.0003050347,0.000009402645,0.0002271878,0.0004677202,0.0001058395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002254486,"about_ca_system_score_gemma":0.0001816421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007299512,"about_ca_topic_score_gemma":6.501263e-7,"domain_scores_codex":[0.9985194,0.0001451535,0.0003235538,0.0003622748,0.0002556951,0.0003939618],"domain_scores_gemma":[0.9989485,0.00001208154,0.0001449736,0.000332633,0.0001705461,0.0003912424],"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":[0.0001491296,0.00007475141,0.0005761341,0.00001945442,0.00005385647,0.0005142558,0.00007890746,0.00001732061,0.9897591,0.000003360518,0.007769989,0.0009837439],"study_design_scores_gemma":[0.002056201,0.0002365032,0.004159425,0.00002573388,0.00002015962,0.008821282,0.00007382454,0.00004029557,0.8643966,0.00001443628,0.1197865,0.0003690085],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931942,0.0003694883,0.00024616,0.0002674043,0.0001085186,0.00008270494,0.00001773446,0.00001871805,0.005695043],"genre_scores_gemma":[0.9921428,0.0009481324,0.001235228,0.0001905866,0.0007386152,0.000001176075,0.00005674518,0.00005092607,0.004635808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1253624,"threshold_uncertainty_score":0.9204828,"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."}}