{"id":"W2263543537","doi":"10.1038/srep15552","title":"Screening and Identifying a Novel ssDNA Aptamer against Alpha-fetoprotein Using CE-SELEX","year":2015,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Natural Science Foundation of China; Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences; Chinese Academy of Sciences; National Science Foundation","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; Alpha (finance); Computational biology; Biology; Bioinformatics; Genetics; Medicine; RNA; 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":[0.001172545,0.000187853,0.0001911602,0.000136497,0.0002671564,0.000237833,0.00009896673,0.0001295991,0.000001447642],"category_scores_gemma":[0.0001761691,0.0001695403,0.00009952918,0.0002616859,0.0003068203,0.00001908214,0.0002183144,0.00009430213,0.000001195182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002318567,"about_ca_system_score_gemma":0.0001051128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000273889,"about_ca_topic_score_gemma":0.00001916817,"domain_scores_codex":[0.9980566,0.00003308582,0.0003787213,0.0008627732,0.0003509187,0.0003178997],"domain_scores_gemma":[0.9986575,0.000003708447,0.0002856769,0.0006386596,0.000228637,0.0001858026],"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":[0.000009038858,0.00002714628,0.0008160108,0.000007724601,0.00002962188,0.00005590992,0.00004520221,0.00002809867,0.9946007,0.00000537923,0.0007473167,0.003627908],"study_design_scores_gemma":[0.0001704315,0.00003021552,0.00007658669,0.00005452418,0.00003627807,0.0003539293,0.0002244395,0.001234066,0.9607946,0.0003893701,0.03636318,0.0002724375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9319851,0.0005478691,0.06610534,0.00004538863,0.0006215761,0.0001932441,0.000002892866,0.00005340726,0.0004452241],"genre_scores_gemma":[0.9248852,0.00001324981,0.07355363,0.00006815507,0.0001340895,0.000004459242,0.00008826996,0.00002205134,0.001230937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03561587,"threshold_uncertainty_score":0.6913653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05115850328491166,"score_gpt":0.3107271589146767,"score_spread":0.259568655629765,"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."}}