{"id":"W2143917214","doi":"10.1007/s002160000683","title":"Influences of non-selective interactions of nucleic acids on response rates of nucleic acid fiber optic biosensors","year":2001,"lang":"en","type":"article","venue":"Fresenius Journal of Analytical Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Credit Valley Hospital; FONA International (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Oligonucleotide; Nucleic acid; Biosensor; Complementary DNA; DNA; Chemistry; Nucleic acid thermodynamics; Hybridization probe; Molecular beacon; Oligomer restriction; DNA–DNA hybridization; Biochemistry; Chromatography; Molecular biology; Biology; Gene; Base sequence","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":[0.002034241,0.0009679588,0.0007724676,0.0003617021,0.0005210012,0.001399478,0.0009782652,0.0008456316,0.001856517],"category_scores_gemma":[0.009015613,0.0008990728,0.0003669627,0.0003380157,0.0005626088,0.001083954,0.0005949322,0.0008137954,0.0007478009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008893806,"about_ca_system_score_gemma":0.0006298306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001581788,"about_ca_topic_score_gemma":0.001395139,"domain_scores_codex":[0.9977323,0.0007229388,0.0001918135,0.0003954495,0.000552297,0.0004050824],"domain_scores_gemma":[0.988301,0.009164519,0.0007503579,0.0004189734,0.0008526346,0.0005124629],"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":[0.0009153295,0.00006074292,0.0002964435,0.00005796804,0.00002100883,0.0000736017,0.0001181409,0.0003123006,0.995363,0.0001038836,0.00004512713,0.002632511],"study_design_scores_gemma":[0.00001164234,0.0001263333,0.000597759,0.000002468419,0.00001482032,0.00003193438,0.00002070894,0.001251132,0.9977055,0.00001526525,0.0002152123,0.000007220477],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931733,0.001025619,0.003919067,0.0001194473,0.00006673205,0.00002888827,0.00008524275,0.00009400206,0.001487801],"genre_scores_gemma":[0.9944586,0.0005964668,0.003109291,0.00009912191,0.00003882829,0.00005588885,0.0001783189,0.0001502954,0.001313195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002034241,"threshold_uncertainty_score":0.01075828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01320385952224101,"score_gpt":0.316461655295013,"score_spread":0.303257795772772,"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."}}