{"id":"W4413373993","doi":"10.1002/anie.202510518","title":"Green Fluorescent Protein SELEX: Immobilization Chemistry and His‐Tag Epitope Bias","year":2025,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Waterloo","funders":"Global Water Futures; Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; Green fluorescent protein; Epitope; Chemistry; Fluorescence; DNA; Target protein; Computational biology; Biophysics; Molecular biology; Biochemistry; Biology; Gene; Genetics; RNA; Antibody","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":[0.001116115,0.0005664811,0.0005464851,0.0002826028,0.0002113259,0.0007051203,0.0004789369,0.0003905153,0.001044906],"category_scores_gemma":[0.0008241,0.0002779507,0.000198204,0.000423704,0.0003563124,0.0003602155,0.0006135283,0.000642375,0.0005339913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002964349,"about_ca_system_score_gemma":0.0002323124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001952444,"about_ca_topic_score_gemma":0.0003787175,"domain_scores_codex":[0.9995306,0.0001379843,0.0000443434,0.00007832776,0.0001570941,0.00005179821],"domain_scores_gemma":[0.9997073,0.0001251121,0.00004398856,0.00005245736,0.00004571596,0.00002540376],"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":[0.000141979,0.0001017269,0.0003730634,0.0001279762,0.00003652444,0.0002117578,0.00009588519,0.0016841,0.9843054,0.000879008,0.000212375,0.01183029],"study_design_scores_gemma":[0.00001215883,0.00006401814,0.0002313385,0.000004554806,0.00001094738,0.0001131872,0.00001830849,0.002942559,0.9947329,0.0001078953,0.001754824,0.000007270151],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8969966,0.0009071238,0.09714337,0.0002890122,0.00005739112,0.0003314842,0.0003864766,0.000466745,0.0034218],"genre_scores_gemma":[0.9196072,0.001443662,0.06943005,0.0002917156,0.00001409768,0.0002750691,0.0005231965,0.0002516614,0.008163308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001116115,"threshold_uncertainty_score":0.005902648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009382003236938736,"score_gpt":0.2643483169601903,"score_spread":0.2549663137232516,"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."}}