{"id":"W4413168948","doi":"10.1016/j.microc.2025.114872","title":"Dual-monomer molecularly imprinted polymer and boron nitride quantum dots for electrochemical sensing of folic acid","year":2025,"lang":"en","type":"article","venue":"Microchemical Journal","topic":"Carbon and Quantum Dots Applications","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Regroupement Québécois sur les Matériaux de Pointe","funders":"Jiangsu University; National Natural Science Foundation of China","keywords":"Molecularly imprinted polymer; Folic acid; Boron nitride; Quantum dot; Monomer; Electrochemistry; Dual (grammatical number); Materials science; Polymer; Nanotechnology; Chemical engineering; Chemistry; Organic chemistry; Selectivity; Composite material; Catalysis; Electrode; Physical chemistry; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002644881,0.0001750829,0.0003180917,0.0001265196,0.0001265896,0.00009325601,0.0001645397,0.0001445545,0.00003563663],"category_scores_gemma":[0.0001114314,0.0001618165,0.0001461958,0.0001855105,0.0001606717,0.00006843745,0.00009528536,0.0002813025,0.000004303354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007235648,"about_ca_system_score_gemma":0.0001383592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002182705,"about_ca_topic_score_gemma":0.000001557166,"domain_scores_codex":[0.9986438,0.00002977269,0.0004943219,0.0002951552,0.0001535675,0.000383404],"domain_scores_gemma":[0.9991754,0.00009876473,0.0001743793,0.0002015551,0.0002003009,0.00014965],"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":[0.0001465182,0.0000513998,0.00002435034,0.00002955863,0.00002750916,0.000002185809,0.00005450114,6.026713e-8,0.9973215,0.001303069,0.0003820772,0.0006572198],"study_design_scores_gemma":[0.0007944437,0.00003829597,0.00005743085,0.00005774347,0.00006958615,0.0002221304,0.00004701491,0.0002978059,0.994913,0.002395733,0.0009494622,0.0001573581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9399971,0.001898115,0.05690149,0.000789367,0.00009265314,0.0001652031,0.00001458261,0.00002691213,0.0001145225],"genre_scores_gemma":[0.9946082,0.00006322505,0.00476437,0.0003628036,0.0001070758,0.000008198648,0.000008260465,0.00001803397,0.00005982775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05461105,"threshold_uncertainty_score":0.6598684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005709853497347043,"score_gpt":0.2542412077871206,"score_spread":0.2485313542897736,"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."}}