{"id":"W2156935100","doi":"10.1002/bit.25294","title":"A simple method for eliminating fixed‐region interference of aptamer binding during SELEX","year":2014,"lang":"en","type":"article","venue":"Biotechnology and Bioengineering","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; Oligonucleotide; Computational biology; SELEX Aptamer Technique; Chemistry; Computer science; Biology; Molecular biology; Biochemistry; DNA; Gene; RNA","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":[0.0001777374,0.0001527203,0.0002053894,0.0001559862,0.00007660832,0.00000771318,0.0001175179,0.0003188626,2.359651e-7],"category_scores_gemma":[0.0001521274,0.0001388005,0.00006988607,0.0001363202,0.00009095437,0.00000437404,0.0001144911,0.0000977005,1.336039e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007898657,"about_ca_system_score_gemma":0.00000547867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004160727,"about_ca_topic_score_gemma":0.000004717488,"domain_scores_codex":[0.9992102,0.00001766284,0.0002033253,0.0003152561,0.00003567712,0.0002178311],"domain_scores_gemma":[0.9995839,0.00002774796,0.0001017433,0.0002094031,0.00004737345,0.00002984127],"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":[0.00002744783,0.00001038007,0.0003374593,0.00007128467,0.00004343713,4.068989e-7,0.000008467519,0.00002282633,0.9815912,0.0003290677,0.00001138266,0.01754668],"study_design_scores_gemma":[0.0002070998,0.0002622991,0.0001707727,0.00004533767,0.0000308037,0.00003182333,0.0000657277,0.007298275,0.990658,0.00006517617,0.0009929095,0.0001717269],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5596601,0.00009684589,0.4399694,0.00009261349,0.00002148769,0.00007785746,0.000005015652,0.00006721518,0.000009482161],"genre_scores_gemma":[0.9185575,0.0001227633,0.08117358,0.00001744871,0.00005369611,0.00001045925,0.00001845005,0.00001557347,0.00003056429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3588974,"threshold_uncertainty_score":0.5660122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00842010722664773,"score_gpt":0.2624089758164521,"score_spread":0.2539888685898044,"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."}}