{"id":"W4405178333","doi":"10.1021/jacsau.4c00890","title":"Quantitative Characterization of Partitioning Stringency in SELEX","year":2024,"lang":"en","type":"article","venue":"JACS Au","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Systematic evolution of ligands by exponential enrichment; Aptamer; Selection (genetic algorithm); Biology; Computer science; Genetics; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00533782,0.0009296511,0.0006924173,0.001033274,0.0004434602,0.001471063,0.001065516,0.001039272,0.0007473236],"category_scores_gemma":[0.01188314,0.0005263715,0.0004041645,0.0009597944,0.001951352,0.001573512,0.001229327,0.00133228,0.0003895641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009711258,"about_ca_system_score_gemma":0.0003902609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000354128,"about_ca_topic_score_gemma":0.0004623543,"domain_scores_codex":[0.9947935,0.001478489,0.0004162183,0.0008708815,0.002195214,0.0002457197],"domain_scores_gemma":[0.9894989,0.006825578,0.001608294,0.001043996,0.000831363,0.0001918546],"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":[0.000119507,0.0000798012,0.001541986,0.0001701401,0.00002934885,0.00006004634,0.0001537227,0.00628929,0.9758437,0.003188079,0.00007916101,0.01244529],"study_design_scores_gemma":[0.00001302471,0.0003466944,0.003292053,0.00002606631,0.00002438589,0.0001129218,0.00005661746,0.0407005,0.9518844,0.002318406,0.001183823,0.00004110944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4487446,0.001414456,0.5449116,0.0004000538,0.00006219507,0.0004083303,0.000325061,0.0006476174,0.003086054],"genre_scores_gemma":[0.8826823,0.00111229,0.113037,0.0002893692,0.00002150673,0.0006843954,0.0003985224,0.0001461954,0.001628428],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00533782,"threshold_uncertainty_score":0.02822942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415996772227444,"score_gpt":0.3023071887988086,"score_spread":0.2881472210765341,"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."}}