{"id":"W4389763659","doi":"10.1101/2023.12.13.571601","title":"Multivalent DNA-encoded lectins on phage enable detecting compositional glycocalyx differences","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Glycomics Network; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fundação de Amparo à Pesquisa do Estado de São Paulo; Alberta Innovates; Conselho Nacional de Desenvolvimento Científico e Tecnológico; University of Alberta","keywords":"Glycocalyx; Lectin; Glycan; DNA; Biology; Phage display; Cell; Epitope; In vitro; Cell biology; Glycomics; Chemistry; Molecular biology; Biochemistry; Glycoprotein; Antigen; Antibody; Immunology","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":[0.0001184234,0.0002436493,0.0001235092,0.0001463163,0.0000969007,0.0002532604,0.000165978,0.0002370202,0.0009903744],"category_scores_gemma":[0.0001025406,0.00007977945,0.0001395216,0.0001136203,0.0001818049,0.000124897,0.0002446234,0.0003598191,0.0003112286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003111912,"about_ca_system_score_gemma":0.000100913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004174481,"about_ca_topic_score_gemma":0.0004839317,"domain_scores_codex":[0.9999177,0.00001112764,0.000003325543,0.00002277536,0.00002250539,0.00002253427],"domain_scores_gemma":[0.9999187,0.00001521695,0.00002168129,0.000009413645,0.00001230763,0.00002268724],"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":[0.00001155531,0.000003153717,0.00004953246,0.000005307375,7.365696e-7,0.000003942635,0.000002769711,0.00001527372,0.9995601,0.0000392071,0.000009857458,0.0002985749],"study_design_scores_gemma":[0.000001876126,0.00004689081,0.0007648676,0.000001463636,0.000002622475,0.00004515952,0.000006313914,0.0005412234,0.9980533,0.00002743921,0.0005067038,0.000002128784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879412,0.0002584433,0.01005457,0.00005036755,0.00001234249,0.00001622343,0.0001856599,0.0001514942,0.001329609],"genre_scores_gemma":[0.9866215,0.0001715892,0.01108167,0.00006219232,0.000004405633,0.00001917485,0.0001995772,0.00002651128,0.001813501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009903744,"threshold_uncertainty_score":0.003313065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.031997511188941,"score_gpt":0.2655963291103288,"score_spread":0.2335988179213878,"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."}}