{"id":"W2896696833","doi":"10.1016/j.talanta.2018.10.063","title":"In vitro selection of CD70 binding aptamer and its application in a biosensor design for sensitive detection of SKOV-3 ovarian cells","year":2018,"lang":"en","type":"article","venue":"Talanta","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Mashhad University of Medical Sciences; Ryerson University","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; Chemistry; Dissociation constant; SELEX Aptamer Technique; In vitro; Molecular biology; Computational biology; Receptor; Biochemistry; Gene; Biology; RNA","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001596919,0.00007353889,0.0001280633,0.0001258271,0.00001972347,0.00000231157,0.00002545699,0.0001053657,9.134565e-8],"category_scores_gemma":[0.00002851499,0.0000711717,0.00002732208,0.0001805346,0.00004847172,0.000004451565,0.00001559907,0.0000319067,2.464473e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001381624,"about_ca_system_score_gemma":0.00001131039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004327929,"about_ca_topic_score_gemma":0.0001502214,"domain_scores_codex":[0.9994554,0.00004130835,0.000169248,0.0001967126,0.00003984143,0.00009747743],"domain_scores_gemma":[0.9996879,0.00001649207,0.0001180205,0.00007315592,0.00009059795,0.00001385791],"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":[0.0003678774,0.00002998274,0.00006289277,0.00001548739,0.00001160026,2.477633e-7,0.00003336572,0.000002270387,0.9964994,0.000004479378,0.000003596881,0.002968827],"study_design_scores_gemma":[0.0002720621,0.0002484544,0.0002264101,0.00001437048,0.00001447201,0.000008796485,0.00004338715,0.002805146,0.9962037,0.00002609341,0.00006135547,0.00007574965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783145,0.00001371869,0.02131667,0.00001469808,0.00001437362,0.0002834838,0.00001594998,0.000006133342,0.00002043223],"genre_scores_gemma":[0.9963957,0.00004332136,0.003435891,0.0000131021,0.00004698693,0.00001070246,0.00001866973,0.000007937827,0.00002769409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01808115,"threshold_uncertainty_score":0.2902298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01040206848301262,"score_gpt":0.2645110504878496,"score_spread":0.254108982004837,"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."}}