{"id":"W4220829642","doi":"10.3390/mi13030436","title":"Multivalent Aptamer Approach: Designs, Strategies, and Applications","year":2022,"lang":"en","type":"review","venue":"Micromachines","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aptamer; Nanotechnology; Avidity; Computational biology; Chemistry; Computer science; Biology; Materials science; Molecular biology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001516825,0.0003917929,0.0006371914,0.00009890939,0.0001959887,0.00006819334,0.0002537083,0.0002272337,0.000005378924],"category_scores_gemma":[0.00001199359,0.0003034435,0.0002904685,0.0001698267,0.000125313,0.000003617558,0.0002645374,0.0002300221,0.000001385111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002271765,"about_ca_system_score_gemma":0.0000935895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001636598,"about_ca_topic_score_gemma":0.000004787069,"domain_scores_codex":[0.9985732,0.0001564352,0.0003177862,0.0006583163,0.00009421764,0.0002000126],"domain_scores_gemma":[0.9991958,0.0000208677,0.0002166769,0.0004843395,0.00002123306,0.00006108635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003824656,0.00008520851,0.000001643921,0.001404449,0.0001829044,0.000001630095,0.000004638003,8.200162e-7,0.002830599,0.00004626729,0.0003947348,0.9950433],"study_design_scores_gemma":[0.00005827865,0.00005168503,6.258465e-7,0.00008904532,0.0003439344,0.00009958688,0.00004269703,0.000008054775,0.0002062873,0.00002784188,0.9987052,0.0003667526],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001487497,0.9937865,0.004794513,0.000003533555,0.00002091996,0.0005970076,0.000122762,0.00005684778,0.0006030252],"genre_scores_gemma":[0.0001247919,0.9888138,0.00765506,0.00003129878,0.000227352,0.0003316058,0.00219834,0.00005683465,0.0005609784],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9983104,"threshold_uncertainty_score":0.9999418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05101349115288517,"score_gpt":0.3421359232703879,"score_spread":0.2911224321175028,"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."}}