{"id":"W2320615728","doi":"10.1021/ac502600a","title":"Quantum Dot-Based Concentric FRET Configuration for the Parallel Detection of Protease Activity and Concentration","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Michael Smith Health Research BC; Canada Foundation for Innovation","keywords":"Förster resonance energy transfer; Chemistry; Cyanine; Aptamer; Protease; Thrombin; Peptide; Alexa Fluor; Biophysics; Bioanalysis; Fluorescence; Nanotechnology; Quantum dot; Combinatorial chemistry; Biochemistry; Enzyme; Molecular biology; Chromatography","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":[0.0006059919,0.0004954221,0.0005845577,0.0002752657,0.0002279772,0.0004374472,0.001318212,0.000982995,0.0007507853],"category_scores_gemma":[0.0007085567,0.0004066572,0.0002848993,0.0003512629,0.0005800289,0.0007731001,0.0006880449,0.0006118174,0.0005918062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007647805,"about_ca_system_score_gemma":0.0003287165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003917818,"about_ca_topic_score_gemma":0.0006083437,"domain_scores_codex":[0.9992292,0.0001422844,0.0000435891,0.0003055894,0.0002232485,0.00005612377],"domain_scores_gemma":[0.9995944,0.0001090215,0.00008206769,0.00007626212,0.00008868177,0.00004954385],"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":[0.00005795765,0.00003283088,0.0001032278,0.000033108,0.000007919776,0.00003950586,0.00001955499,0.0004868822,0.9949502,0.0007502885,0.00009174637,0.003426753],"study_design_scores_gemma":[0.000009691611,0.00008878053,0.0002144014,0.000001916906,0.000008799437,0.0002429178,0.000006476805,0.01426877,0.9838176,0.0001449394,0.001178301,0.00001747769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6739987,0.001228382,0.318629,0.0003373077,0.0001501838,0.0001726348,0.0003406419,0.00134698,0.003796157],"genre_scores_gemma":[0.7838226,0.0005312748,0.2125134,0.000176479,0.0000269957,0.0001447293,0.0002300621,0.00004795845,0.002506462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001318212,"threshold_uncertainty_score":0.005548954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0101842227549819,"score_gpt":0.266720299695731,"score_spread":0.2565360769407491,"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."}}