{"id":"W4387700235","doi":"10.1002/ange.202314248","title":"Fluorogenic Photo‐Crosslinking of Glycan‐Binding Protein Recognition Using a Fluorinated Azido‐Coumarin Fucoside","year":2023,"lang":"en","type":"article","venue":"Angewandte Chemie","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Centre National de la Recherche Scientifique; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation","keywords":"Glycan; Chemistry; Chromophore; Covalent bond; Photoaffinity labeling; Combinatorial chemistry; Coumarin; Benzophenone; Fluorescence; Affinities; Scaffold; Fluorophore; Binding site; Stereochemistry; Biochemistry; Photochemistry; 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":[0.0002113472,0.0003373263,0.0001025458,0.0001702939,0.0001512808,0.0001519585,0.0002815531,0.0003272044,0.000716656],"category_scores_gemma":[0.0001409653,0.00009608849,0.0001693051,0.0001739328,0.0002696148,0.0001521933,0.0001464055,0.0004208359,0.0001700392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003731409,"about_ca_system_score_gemma":0.0001172856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000871839,"about_ca_topic_score_gemma":0.0006930967,"domain_scores_codex":[0.9998876,0.00002689888,0.000003616663,0.00003277562,0.00001833877,0.00003084289],"domain_scores_gemma":[0.9999005,0.00003232494,0.00002797141,0.00001513891,0.000009006855,0.00001504396],"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":[0.00002058752,0.00001002965,0.00003761922,0.0000172708,0.000002872464,0.00002977904,0.00001077037,0.0001328321,0.9991454,0.0001339825,0.00002407269,0.0004348781],"study_design_scores_gemma":[0.000001691125,0.00003733248,0.0003454843,0.000001292971,0.000002497416,0.00004303828,0.000004067341,0.0004245251,0.9986805,0.00001789205,0.0004400318,0.000001666644],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740893,0.0009678319,0.02192921,0.000133725,0.00002948382,0.00002466315,0.0001187071,0.0001080378,0.002598971],"genre_scores_gemma":[0.9926744,0.0004158097,0.005657538,0.00005817116,0.000005230982,0.00001277817,0.00009350513,0.00001051436,0.001072132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000871839,"threshold_uncertainty_score":0.002707362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04893983468184935,"score_gpt":0.3046679760738352,"score_spread":0.2557281413919859,"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."}}