{"id":"W4415268113","doi":"10.1039/d5cc04872a","title":"Combining aptamers for thiamphenicol and chloramphenicol for detecting both antibiotics","year":2025,"lang":"en","type":"article","venue":"Chemical Communications","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"China Scholarship Council; University of Waterloo; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Thiamphenicol; Aptamer; Chloramphenicol; Isothermal titration calorimetry; Dissociation constant; Titration","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":[0.0005969492,0.0009663997,0.0003647604,0.0004802554,0.000237517,0.0003850079,0.0005525737,0.001392768,0.003778205],"category_scores_gemma":[0.0006713889,0.0004594027,0.0002674657,0.0004027476,0.0003054604,0.0003443428,0.0004389474,0.0009135763,0.002024742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004031388,"about_ca_system_score_gemma":0.0003046455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000591032,"about_ca_topic_score_gemma":0.002137013,"domain_scores_codex":[0.9993435,0.0001113723,0.00003530057,0.0001858141,0.0002035045,0.0001205701],"domain_scores_gemma":[0.9996358,0.0001127965,0.00005205167,0.00004341741,0.00007595832,0.00007992655],"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":[0.00001418833,0.0000102904,0.00003743379,0.0000241628,0.000002435061,0.00001073564,0.000006847348,0.00001940138,0.9989012,0.0000219009,0.00005556542,0.000895961],"study_design_scores_gemma":[0.00001178369,0.0001171664,0.0006467727,0.000008375163,0.0000142175,0.00012416,0.00001179266,0.0005442753,0.9960908,0.00002837532,0.002396459,0.000005727406],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8639372,0.00792806,0.1082042,0.0005760753,0.0004700238,0.0005283134,0.001160823,0.001990492,0.01520479],"genre_scores_gemma":[0.876885,0.002009194,0.1024653,0.0006691738,0.00007513831,0.0005460497,0.001787879,0.0001262938,0.01543601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003778205,"threshold_uncertainty_score":0.0126394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0222761121432167,"score_gpt":0.3319936084369767,"score_spread":0.30971749629376,"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."}}