{"id":"W2320263721","doi":"10.1021/ac503639s","title":"Aptamer-Based Label-Free Impedimetric Biosensor for Detection of Progesterone","year":2014,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Aptamer; Chemistry; Biosensor; Dissociation constant; Oligonucleotide; Circular dichroism; Dielectric spectroscopy; Biophysics; DNA; Combinatorial chemistry; Biochemistry; Molecular biology; Electrochemistry; Electrode; Receptor; Biology","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":[0.0003618503,0.0007149452,0.0005637489,0.0002914417,0.0001612739,0.0002550638,0.0009044536,0.001107178,0.0008737381],"category_scores_gemma":[0.0006323581,0.0003677993,0.0002898537,0.0003029566,0.0002692362,0.0004209697,0.0004332693,0.000943996,0.0007161812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003705519,"about_ca_system_score_gemma":0.0001938498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002545864,"about_ca_topic_score_gemma":0.0004809934,"domain_scores_codex":[0.9993586,0.0001240012,0.00004206274,0.0001751588,0.000250384,0.00004974044],"domain_scores_gemma":[0.9997889,0.00008772587,0.00003629102,0.00001601373,0.00004872265,0.0000223872],"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":[0.0000232676,0.00001072043,0.0000476381,0.00004882667,0.000003532222,0.00001762238,0.00000995637,0.00005987049,0.9976727,0.0000409282,0.00003910252,0.002025768],"study_design_scores_gemma":[0.00001030901,0.0001572725,0.0004483746,0.000004429573,0.00001245167,0.0001938248,0.00001603919,0.00283107,0.9942549,0.0000539718,0.002006271,0.00001118321],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6226144,0.01582629,0.3529311,0.0009477311,0.0006074805,0.0003765348,0.0007764135,0.00181409,0.004105884],"genre_scores_gemma":[0.6805061,0.006756947,0.3007036,0.0005703676,0.0001195245,0.000449259,0.0005730913,0.00006328578,0.01025788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001107178,"threshold_uncertainty_score":0.002922952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132629512761064,"score_gpt":0.272945189368726,"score_spread":0.2616188942411154,"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."}}