{"id":"W2112010689","doi":"10.1002/anie.200461848","title":"In Vitro Selection of Structure‐Switching Signaling Aptamers","year":2005,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":443,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Aptamer; DNA; Systematic evolution of ligands by exponential enrichment; Computational biology; Selection (genetic algorithm); In vitro; Fluorophore; Chemistry; Isolation (microbiology); Fluorescence; Nanotechnology; Computer science; Molecular biology; Biology; Bioinformatics; Biochemistry; RNA; Materials science; Gene; Physics; Artificial intelligence","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":[0.0003877832,0.000433022,0.0002993773,0.0001761632,0.0001358918,0.0004176079,0.0003070588,0.0002792426,0.001067117],"category_scores_gemma":[0.0003487238,0.0002286954,0.0002173375,0.0001399064,0.0001586619,0.0001522615,0.000262678,0.0007467207,0.0008897981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002741646,"about_ca_system_score_gemma":0.0001461774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000218374,"about_ca_topic_score_gemma":0.0004377912,"domain_scores_codex":[0.999673,0.00008213679,0.00002563756,0.00007539739,0.00009205414,0.0000518225],"domain_scores_gemma":[0.9997489,0.0001004395,0.00004785433,0.00003454874,0.00002933249,0.00003895244],"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":[0.00001118209,0.000009644035,0.00002688133,0.000006492309,0.000001268052,0.000009700201,0.000006231981,0.00005015277,0.9991999,0.00007246581,0.00003982897,0.0005661797],"study_design_scores_gemma":[0.000002267792,0.0000228271,0.00007386416,5.281416e-7,0.000002458436,0.00003055632,0.000001723295,0.0003449862,0.998422,0.00001116514,0.001086078,0.000001554246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8261176,0.001171445,0.1648526,0.000286151,0.0002355797,0.0002040132,0.001150661,0.001185668,0.00479629],"genre_scores_gemma":[0.9090554,0.001121765,0.07533383,0.0002590396,0.0000591181,0.0001903007,0.002376255,0.0002550902,0.01134915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001067117,"threshold_uncertainty_score":0.003569901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006563369563021753,"score_gpt":0.2663818450970311,"score_spread":0.2598184755340093,"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."}}