{"id":"W1996874298","doi":"10.1016/j.trac.2013.12.014","title":"DNA-stabilized, fluorescent, metal nanoclusters for biosensor development","year":2014,"lang":"en","type":"article","venue":"TrAC Trends in Analytical Chemistry","topic":"Nanocluster Synthesis and Applications","field":"Materials Science","cited_by":209,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Nanoclusters; Biosensor; Aptamer; Fluorescence; DNA; Metal ions in aqueous solution; Quantum yield; Nucleic acid; Nanotechnology; Combinatorial chemistry; Chemistry; Metal; Quenching (fluorescence); Materials science; Organic chemistry; Biochemistry; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002520439,0.0002333358,0.0002289273,0.0002252674,0.000171135,0.0004505322,0.0005323369,0.0005372228,0.001365687],"category_scores_gemma":[0.0004721397,0.0002116915,0.0001496165,0.0001762154,0.0002370582,0.0004097641,0.0002703956,0.0005420651,0.000547579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000904433,"about_ca_system_score_gemma":0.0003108457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006723938,"about_ca_topic_score_gemma":0.001697709,"domain_scores_codex":[0.9998009,0.00002597368,0.00001243126,0.00006595598,0.00006682873,0.00002801592],"domain_scores_gemma":[0.9998677,0.00003413932,0.00003092935,0.00001565448,0.00003032609,0.00002139726],"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":[0.00003952052,0.00001296402,0.00004702139,0.00006076466,0.000004152764,0.00001931287,0.00001901124,0.0001499952,0.9926265,0.0006170476,0.0001935025,0.006210257],"study_design_scores_gemma":[0.000006088056,0.00002901022,0.00005950797,0.000002801316,0.000003692226,0.00002604853,0.000004740732,0.001029851,0.9969951,0.00004766039,0.001792943,0.000002645453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7768716,0.01155561,0.1937351,0.001740378,0.000377241,0.0002863575,0.000789498,0.002045766,0.01259852],"genre_scores_gemma":[0.930531,0.001921831,0.05864405,0.0003035675,0.00003359377,0.0001272273,0.0003281938,0.00008700591,0.008023513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001365687,"threshold_uncertainty_score":0.006562114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02508556534761804,"score_gpt":0.2823205631685207,"score_spread":0.2572349978209026,"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."}}