{"id":"W2782156804","doi":"10.1002/cpch.28","title":"In Vitro Selection and Characterization of DNA Aptamers to a Small Molecule Target","year":2017,"lang":"en","type":"article","venue":"Current Protocols in Chemical Biology","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Aptamer; Oligonucleotide; Computational biology; Systematic evolution of ligands by exponential enrichment; Small molecule; DNA; Selection (genetic algorithm); Characterization (materials science); Biology; Nanotechnology; Chemistry; Molecular biology; Genetics; Computer science; Gene; RNA; Materials science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006281296,0.0005288326,0.0005454973,0.0002747895,0.0002471433,0.0003413811,0.0003629285,0.0002717208,0.001535987],"category_scores_gemma":[0.0006607365,0.0003499712,0.0003512182,0.0003106386,0.0002194029,0.0001510954,0.0002979613,0.0008033645,0.001959588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003078335,"about_ca_system_score_gemma":0.0003671442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005856181,"about_ca_topic_score_gemma":0.001085498,"domain_scores_codex":[0.9994591,0.0001177065,0.00008112551,0.000106288,0.0001535525,0.00008221505],"domain_scores_gemma":[0.9996315,0.0001384358,0.00005431409,0.00005676071,0.00007625244,0.00004265985],"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":[0.000008507358,0.000009843996,0.00002533637,0.0000161725,0.000001386392,0.00001317436,0.00001013171,0.00008637,0.9992999,0.00004350127,0.00002716729,0.0004584876],"study_design_scores_gemma":[0.000002137582,0.00005562784,0.0001703937,0.000002994523,0.000004771918,0.00002760262,0.000004884214,0.0005319724,0.9961837,0.00001487412,0.002998883,0.000002160578],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7223046,0.003220849,0.2572706,0.0003652937,0.0003630259,0.001363039,0.003026158,0.0008616601,0.01122467],"genre_scores_gemma":[0.7704522,0.005892966,0.1807926,0.0005549493,0.000117606,0.001940909,0.01009763,0.0004521078,0.02969914],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001535987,"threshold_uncertainty_score":0.005138397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322560554489086,"score_gpt":0.3502923522717322,"score_spread":0.3270667467268413,"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."}}