{"id":"W2766594038","doi":"10.1002/cbic.201700498","title":"Ultrasensitive DNAzyme‐Based Ca<sup>2+</sup> Detection Boosted by Ethanol and a Solvent‐Compatible Scaffold for Aptazyme Design","year":2017,"lang":"en","type":"article","venue":"ChemBioChem","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Waterloo","keywords":"Deoxyribozyme; Aptamer; Biosensor; Metal ions in aqueous solution; Chemistry; DNA; Selectivity; Detection limit; Combinatorial chemistry; G-quadruplex; Aqueous solution; Solvent; Ethanol; Nanotechnology; Biophysics; Ion; Biochemistry; Chromatography; Organic chemistry; Materials science; Molecular biology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002489146,0.0003034372,0.0002885862,0.00005265757,0.0004874713,0.0001167411,0.0002056532,0.0003343347,0.000001512294],"category_scores_gemma":[0.0002753427,0.0002933916,0.0001667546,0.00005403604,0.0002508272,0.00001332811,0.00008100935,0.00009982936,0.000001970094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003182345,"about_ca_system_score_gemma":0.00004762244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003343284,"about_ca_topic_score_gemma":0.00001033156,"domain_scores_codex":[0.9985816,0.00004195743,0.0002320723,0.0006458794,0.0001309976,0.000367435],"domain_scores_gemma":[0.9987368,0.00003867023,0.0002327544,0.000643744,0.0002157189,0.0001323003],"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":[0.0002361821,0.00007092426,0.00004468341,0.00003091849,0.00008705209,0.00000186108,0.00002630135,0.00001614974,0.9932092,0.000001368395,0.002953959,0.00332138],"study_design_scores_gemma":[0.0009837566,0.0003732188,0.000028976,0.00003762348,0.00009586006,0.00001146675,0.00008881152,0.007548823,0.9883096,0.00005049688,0.002087056,0.0003843732],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9164521,0.0004403111,0.08158065,0.0003940529,0.00004398373,0.0006388657,0.0001421932,0.00009168157,0.0002162004],"genre_scores_gemma":[0.99101,0.00005978777,0.007484678,0.0003520036,0.0001572227,0.00006030308,0.0003414593,0.00004239486,0.00049221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07455789,"threshold_uncertainty_score":0.9999518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01971877503528348,"score_gpt":0.2777306007923087,"score_spread":0.2580118257570252,"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."}}