{"id":"W2737414369","doi":"10.1261/rna.062166.117","title":"Ribonucleoprotein purification and characterization using RNA Mango","year":2017,"lang":"en","type":"article","venue":"RNA","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Institute of General Medical Sciences; Boise State University; University of Wisconsin-Madison; Wisconsin Alumni Research Foundation; Gordon and Betty Moore Foundation; Research Corporation for Science Advancement; National Institutes of Health; National Science Foundation","keywords":"RNA; Biology; Ribonucleoprotein; Aptamer; Biochemistry; Small nuclear RNA; RNA-dependent RNA polymerase; Oligonucleotide; Molecular biology; Computational biology; DNA; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001145116,0.00007370323,0.00006364623,0.00001553027,0.0002491487,0.00008982496,0.0001224015,0.00009074036,0.00001521742],"category_scores_gemma":[0.00004266786,0.00007290172,0.00002258641,0.000009205715,0.00003390276,0.000008908824,0.0000578724,0.00002490881,0.000007885675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004376898,"about_ca_system_score_gemma":0.0000119469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002151904,"about_ca_topic_score_gemma":0.00000268114,"domain_scores_codex":[0.9995527,0.00002233688,0.00008401165,0.0001842086,0.00005688974,0.00009983393],"domain_scores_gemma":[0.9994401,0.000001071051,0.0001220507,0.0003712773,0.0000271747,0.00003833717],"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":[0.00001455559,0.000007189291,0.0002020174,0.00000865028,0.000007134804,6.776662e-7,0.00001249111,2.650237e-7,0.9568041,0.0001826967,0.000006691963,0.04275351],"study_design_scores_gemma":[0.0001015899,0.00003378274,0.01251671,0.0000159527,0.000007932736,0.000004900001,0.000004774751,0.0001248256,0.9816159,0.000169739,0.00530619,0.0000977051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989003,0.000104634,0.009689167,0.0002069841,0.00008751275,0.0001585429,0.000007873203,0.000007290776,0.0007349936],"genre_scores_gemma":[0.9971731,0.0001212001,0.001803349,0.00005758652,0.0002140622,0.00001171119,0.00003441064,0.00001382823,0.0005707828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04265581,"threshold_uncertainty_score":0.2972846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02098333812202518,"score_gpt":0.2578536237452345,"score_spread":0.2368702856232093,"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."}}