{"id":"W2430232674","doi":"10.1038/nprot.2016.071","title":"Electrochemical detection of nucleic acids, proteins, small molecules and cells using a DNA-nanostructure-based universal biosensing platform","year":2016,"lang":"en","type":"article","venue":"Nature Protocols","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":389,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Biosensor; Nucleic acid; DNA; Nanostructure; Nanotechnology; Computational biology; Small molecule; DNA nanotechnology; Chemistry; Biophysics; Biology; Biochemistry; Materials science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001067582,0.0002230938,0.0002179737,0.00009922666,0.00007587454,0.00001852447,0.0001169077,0.0006056385,5.071167e-7],"category_scores_gemma":[0.00008469402,0.0001562018,0.0001047199,0.0001574358,0.0001730496,0.000007979218,0.00006736006,0.0001974273,1.698305e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004323042,"about_ca_system_score_gemma":0.00007802076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000354112,"about_ca_topic_score_gemma":0.00001610564,"domain_scores_codex":[0.9989276,0.00004265064,0.0002183688,0.000417398,0.000143203,0.0002507832],"domain_scores_gemma":[0.9992682,0.00001411918,0.0002016426,0.0002835959,0.0001640811,0.00006830716],"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":[0.0004352565,0.00002784679,0.00007605493,0.00004474767,0.00003229371,0.000002430767,0.000003320514,7.382133e-7,0.9947489,0.00001567818,0.000005269947,0.004607458],"study_design_scores_gemma":[0.0007012123,0.000378583,0.00005233335,0.0001801567,0.0000299706,0.0000213811,0.000006465609,0.0001302284,0.9966201,0.0001572614,0.001491993,0.0002302783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9459139,0.00006610052,0.04449542,0.00007467999,0.00001825256,0.009327201,0.00002051431,0.00005705967,0.00002688226],"genre_scores_gemma":[0.9544568,0.000006894948,0.04502028,0.00009157038,0.00008040728,0.0002933822,0.00001009172,0.00002655232,0.00001403424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009033819,"threshold_uncertainty_score":0.6369726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008101621633010524,"score_gpt":0.2566430368443015,"score_spread":0.2485414152112909,"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."}}