{"id":"W4213018117","doi":"10.1007/s41664-022-00215-1","title":"Special Topic: DNA-Based Biosensors","year":2022,"lang":"en","type":"article","venue":"Journal of Analysis and Testing","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Biosensor; Computational biology; DNA; Computer science; Nanotechnology; Biology; Genetics; 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":[0.0004048413,0.00008734471,0.0002241348,0.0002405829,0.0001883601,0.0000236706,0.00009798001,0.00003111886,0.00001199518],"category_scores_gemma":[0.0001817516,0.00007199701,0.0002364487,0.0005789109,0.00004042988,0.000002946693,0.00006690763,0.0001197322,7.778943e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001347273,"about_ca_system_score_gemma":0.0000402102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006093176,"about_ca_topic_score_gemma":0.00001027644,"domain_scores_codex":[0.9991815,0.00007438406,0.00030142,0.000143381,0.0001872569,0.0001120628],"domain_scores_gemma":[0.9992903,0.00003318685,0.0003531285,0.0001205539,0.0001482815,0.00005447741],"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":[0.0001579896,0.0002104526,0.1750015,0.00001205752,0.001596347,0.0001061655,0.000044209,0.002942698,0.7671961,0.00002995601,0.002113643,0.05058895],"study_design_scores_gemma":[0.001531145,0.003368576,0.05854005,0.0000333961,0.004483321,0.0004636621,0.0008193312,0.006153404,0.8203145,0.0003032344,0.103103,0.0008863743],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975138,0.0001177122,0.001584291,0.0001661291,0.00006066518,0.0000204118,0.000004857027,0.00000561712,0.0005265002],"genre_scores_gemma":[0.9860707,0.00001654283,0.01258371,0.0001896776,0.0009917468,5.098566e-7,0.000009506569,0.000005855545,0.0001317404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1164614,"threshold_uncertainty_score":0.2935953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389070301531685,"score_gpt":0.2605265611142804,"score_spread":0.2466358580989635,"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."}}