{"id":"W4406062796","doi":"10.1016/j.colsurfa.2025.136112","title":"Unveiling the host-guest interactions: CC2 nanocage as an advanced sensor for detection of nitrogenous bases in DNA","year":2025,"lang":"en","type":"article","venue":"Colloids and Surfaces A Physicochemical and Engineering Aspects","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Kazan Federal University; Alliance of International Science Organizations; National Natural Science Foundation of China; Beijing National Laboratory for Molecular Sciences; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Nanocages; DNA; Chemistry; Nanotechnology; Host (biology); Computational biology; Biology; Materials science; Biochemistry; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001616785,0.0002855381,0.0001879631,0.0001087883,0.0001975576,0.0002989116,0.0002374301,0.0005120848,0.0009189555],"category_scores_gemma":[0.0001995778,0.0001148115,0.0001176972,0.00007698825,0.0003099112,0.0004544041,0.000242632,0.0003650424,0.0001735137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003541032,"about_ca_system_score_gemma":0.0002739767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001780632,"about_ca_topic_score_gemma":0.003165507,"domain_scores_codex":[0.9998852,0.00001300816,0.000004232962,0.00003242213,0.00004110994,0.0000239045],"domain_scores_gemma":[0.9999051,0.00002618327,0.00001662822,0.000009956936,0.0000197811,0.00002231213],"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":[0.00004099613,0.000006185265,0.00007142267,0.00002100908,0.000002236108,0.00002755914,0.00001588557,0.00007635456,0.9989161,0.000146889,0.00003802929,0.0006372333],"study_design_scores_gemma":[0.000004731589,0.00007624377,0.0004763073,0.000002009792,0.000005170602,0.0000522154,0.00001563003,0.002765508,0.995509,0.00004383249,0.001043098,0.000006095184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919237,0.0009706363,0.004880785,0.0001925366,0.00005501954,0.00001645988,0.00005787251,0.00008608025,0.001816845],"genre_scores_gemma":[0.995804,0.0003091685,0.002711583,0.00009374358,0.00001855549,0.00001150085,0.00003652327,0.00001678375,0.0009981656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001780632,"threshold_uncertainty_score":0.003540516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004293359135522269,"score_gpt":0.2414669006552217,"score_spread":0.2371735415196994,"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."}}