{"id":"W2273728570","doi":"10.1007/s12274-015-0893-9","title":"Enhanced destabilization of mismatched DNA using gold nanoparticles offers specificity without compromising sensitivity for nucleic acid analyses","year":2015,"lang":"en","type":"article","venue":"Nano Research","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; QIMR Berghofer Medical Research Institute","keywords":"Colloidal gold; Multiplex; DNA microarray; DNA; Nucleic acid; Nucleic acid thermodynamics; Oligonucleotide; Chemistry; genomic DNA; DNA–DNA hybridization; Molecular biology; Computational biology; Base pair; Assay sensitivity; Hybridization probe; Nucleotide; Nanoparticle; Nanotechnology; Biology; Genetics; Biochemistry; Materials science; Base sequence; Gene; Gene expression","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":[],"consensus_categories":[],"category_scores_codex":[0.001545439,0.0001465382,0.0002873642,0.0001406285,0.0001180052,0.00003611517,0.0001234823,0.0001592078,7.930497e-7],"category_scores_gemma":[0.0007224953,0.0001297031,0.0001159843,0.0004248624,0.0003290959,0.00001145748,0.000111034,0.00009388805,7.509746e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006621126,"about_ca_system_score_gemma":0.0001589052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005470317,"about_ca_topic_score_gemma":0.000081444,"domain_scores_codex":[0.9981607,0.0003685138,0.0002965271,0.0004180551,0.0003916016,0.0003645776],"domain_scores_gemma":[0.9981611,0.00006360641,0.0001289691,0.0003933907,0.001132498,0.0001204417],"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":[0.0003563036,0.0001018358,0.0006264537,0.00003526693,0.00003718086,9.460002e-7,0.00007551982,0.0001329732,0.9976997,0.00001062775,0.00009088429,0.0008323333],"study_design_scores_gemma":[0.000416366,0.0002703718,0.0001012133,0.00004056639,0.0000320801,0.000004109974,0.0005185321,0.003521873,0.9947085,0.0001455051,0.00009071118,0.0001502079],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727573,0.0001009083,0.02658738,0.00003830283,0.00002651593,0.0003422506,0.00001942499,0.00002676084,0.0001011885],"genre_scores_gemma":[0.9798859,0.00002827666,0.01984328,0.0000121869,0.00008860463,0.000006253943,0.00005096804,0.00002435461,0.00006015912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007128655,"threshold_uncertainty_score":0.5289138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.201887458189762,"score_gpt":0.4449544540235255,"score_spread":0.2430669958337635,"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."}}