{"id":"W1504153898","doi":"10.1186/1472-6750-5-10","title":"Detection of target DNA using fluorescent cationic polymer and peptide nucleic acid probes on solid support","year":2005,"lang":"en","type":"article","venue":"BMC Biotechnology","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre hospitalier universitaire de Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Génome Québec; Genome Canada","keywords":"Nucleic acid; Peptide nucleic acid; Biology; DNA microarray; DNA; Fluorescence; Nucleic acid quantitation; Cationic polymerization; Nucleic acid thermodynamics; Molecular beacon; Biochemistry; Hybridization probe; Combinatorial chemistry; Molecular biology; Computational biology; Oligonucleotide; Gene; Chemistry; Gene expression; Base sequence; Organic chemistry","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":[0.000444787,0.0005020407,0.0003447429,0.0004778839,0.0002716903,0.0004915213,0.0006504256,0.001205049,0.00174338],"category_scores_gemma":[0.0007025485,0.0002976033,0.0003270014,0.0003901283,0.0005581676,0.0005271158,0.0004985328,0.0006180701,0.001411986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004907706,"about_ca_system_score_gemma":0.0003819976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002955877,"about_ca_topic_score_gemma":0.000400928,"domain_scores_codex":[0.9992927,0.0000708914,0.00003471614,0.000175693,0.000362624,0.00006332776],"domain_scores_gemma":[0.9994386,0.0002282083,0.0001050491,0.00003843295,0.00009320259,0.00009644652],"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":[0.00003384211,0.0000190997,0.00008599782,0.00007125895,0.000004078983,0.00005959401,0.00001205322,0.0001546401,0.9973632,0.0001610136,0.00004002174,0.001995255],"study_design_scores_gemma":[0.000009200749,0.0001215666,0.0002311191,0.000005700424,0.000004549158,0.0001548158,0.000008018235,0.001282043,0.9971585,0.00009489224,0.0009236255,0.000006011529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8458872,0.002594108,0.1442393,0.0005209816,0.0001295818,0.0002391961,0.0003488983,0.0006719898,0.005368758],"genre_scores_gemma":[0.847334,0.002175204,0.1401907,0.0003028071,0.00007370714,0.0002991158,0.0007757896,0.00008570513,0.008762882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00174338,"threshold_uncertainty_score":0.005832195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003916390295026,"score_gpt":0.26172317511146,"score_spread":0.2516840112085098,"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."}}