{"id":"W2033919299","doi":"10.1021/ac702567x","title":"Aptamer-Modified Monolithic Capillary Chromatography for Protein Separation and Detection","year":2008,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Cancer Institute; Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Aptamer; Chromatography; Monolithic HPLC column; Affinity chromatography; Ionic strength; Biotinylation; Elution; Thrombin; Human serum albumin; High-performance liquid chromatography; Biochemistry; Platelet; Molecular biology","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":[0.00008120925,0.000146212,0.0001531857,0.00002555587,0.0001426316,0.00001325422,0.00006040903,0.0002232199,0.000001022929],"category_scores_gemma":[0.00007906657,0.000135181,0.0001255342,0.0001079462,0.0001820344,0.00000438206,0.00003199368,0.00008138514,4.881744e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001076038,"about_ca_system_score_gemma":0.00002533177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006493337,"about_ca_topic_score_gemma":0.000003182196,"domain_scores_codex":[0.9991766,0.00001309682,0.0001785202,0.0003587484,0.00009259324,0.000180476],"domain_scores_gemma":[0.9995324,0.000007226612,0.00006331398,0.0002197999,0.000092733,0.00008453809],"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":[0.00006468361,0.00003030847,0.0001947125,0.00003462419,0.00005435228,0.000002087701,0.000004441374,0.000002273151,0.9987073,0.00001445229,0.0001751325,0.0007156261],"study_design_scores_gemma":[0.0002325252,0.0000947649,0.0002402837,0.000009468413,0.00004114131,0.00005366623,0.00001456734,0.001971387,0.9944741,0.0002018767,0.002480446,0.0001857754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985199,0.0001909063,0.01368953,0.00007904256,0.000007091477,0.0001594946,0.000008236452,0.00004744205,0.0006192381],"genre_scores_gemma":[0.9973578,0.0001271149,0.001570942,0.00007343843,0.0001502961,0.0000325422,0.00009246854,0.0000143247,0.0005810955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01215876,"threshold_uncertainty_score":0.5512522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345659121226498,"score_gpt":0.277919896758734,"score_spread":0.264463305546469,"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."}}