{"id":"W4411668535","doi":"10.3389/fsci.2025.1458636","title":"NANOSPRESSO: toward personalized, locally produced nucleic acid nanomedicines","year":2025,"lang":"en","type":"article","venue":"Frontiers in Science","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Nucleic acid; Computational biology; Computer science; Chemistry; Biology; Biochemistry","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":[0.001822256,0.0006672289,0.0003677557,0.0005906702,0.0005398724,0.002490483,0.0006921241,0.001807179,0.006449086],"category_scores_gemma":[0.001481126,0.0003774925,0.0004287437,0.0003188447,0.001630938,0.002541111,0.003176303,0.002628308,0.003137552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007746067,"about_ca_system_score_gemma":0.001348617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003150735,"about_ca_topic_score_gemma":0.0004493336,"domain_scores_codex":[0.9988019,0.0002599391,0.00003625246,0.0002000876,0.0005669817,0.0001348015],"domain_scores_gemma":[0.9994345,0.0001538924,0.0000884356,0.00005014374,0.0001009396,0.0001720961],"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":[0.0005834046,0.0004104286,0.0008786543,0.001697429,0.0000541721,0.001197512,0.001144138,0.005968106,0.4409701,0.1765006,0.06217351,0.3084219],"study_design_scores_gemma":[0.0001155166,0.0007822515,0.0002862354,0.0002272673,0.00002174521,0.001022512,0.0001804173,0.005046954,0.2270535,0.01130283,0.7538998,0.00006107094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1682961,0.06763636,0.4415755,0.03904446,0.006840297,0.001250064,0.00198489,0.009875116,0.2634973],"genre_scores_gemma":[0.4799956,0.06463339,0.2532486,0.01503745,0.002506369,0.001062642,0.002615225,0.002974288,0.1779265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006449086,"threshold_uncertainty_score":0.02157432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006985481361087361,"score_gpt":0.2737885146273378,"score_spread":0.2668030332662505,"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."}}