{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000998275,0.0001585535,0.000187438,0.0001612498,0.00008031362,0.000007596449,0.0001128031,0.0004327427,0.000002882738],"category_scores_gemma":[0.00004769494,0.0001438359,0.00007197362,0.0001418155,0.0002508051,0.000004765724,0.00009195597,0.0001176227,0.000002626863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002992061,"about_ca_system_score_gemma":0.00004203362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001038693,"about_ca_topic_score_gemma":0.00009195207,"domain_scores_codex":[0.9990593,0.00003085285,0.000246522,0.0003661767,0.00008138105,0.0002157316],"domain_scores_gemma":[0.9993974,0.000004218689,0.0001548724,0.0003542165,0.0000539685,0.00003531457],"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":[0.00005264164,0.00006349352,0.0003060516,0.00001308024,0.00002679013,4.994953e-7,0.00000640019,0.00001284651,0.9910549,0.00008769877,0.00003211678,0.008343499],"study_design_scores_gemma":[0.0001905506,0.0004136851,0.0002236373,0.00001390678,0.0000285656,0.00004330974,0.0000310288,0.0007038706,0.9959022,0.00006462938,0.002225519,0.0001591315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840808,0.0004055521,0.01486408,0.0003208008,0.00003200841,0.0001509134,0.00001120821,0.00008327355,0.00005136566],"genre_scores_gemma":[0.9742208,0.0002128774,0.02524452,0.0001059282,0.00008535263,0.000005128535,0.00002576264,0.00001879909,0.00008080532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01038044,"threshold_uncertainty_score":0.5865459,"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."}}