{"id":"W4405231726","doi":"10.1021/jacs.4c11380","title":"Random Sanitization in DNA Information Storage Using CRISPR-Cas12a","year":2024,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; Shanghai Municipal Education Commission; National Natural Science Foundation of China","keywords":"CRISPR; Chemistry; Metadata; DNA; Oligonucleotide; Computational biology; Computer science; Nanotechnology; Gene; Operating system; Biology","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":[0.0006190502,0.0004823876,0.0004148532,0.0003799961,0.0004310526,0.0007130763,0.0007239112,0.0005489141,0.001032668],"category_scores_gemma":[0.001210884,0.000314725,0.0004163226,0.0002520069,0.0006517569,0.0006694143,0.0007172046,0.0007329939,0.0005814496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005769575,"about_ca_system_score_gemma":0.0005130092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006264673,"about_ca_topic_score_gemma":0.0009633872,"domain_scores_codex":[0.9990603,0.0001023365,0.0001178077,0.0002930101,0.0003152339,0.0001112631],"domain_scores_gemma":[0.9992199,0.0001507219,0.0002567722,0.0002127657,0.0001085349,0.00005124437],"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":[0.00007007142,0.00002984888,0.0004484714,0.0001125227,0.00001435503,0.00007716977,0.00005614605,0.0009693659,0.9857466,0.001553444,0.0002556329,0.01066643],"study_design_scores_gemma":[0.000003308456,0.00005574179,0.0001591017,0.000004016012,0.000004895848,0.00008902493,0.00001018412,0.002452621,0.9949026,0.0001259547,0.002183791,0.000008839015],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7373142,0.002308295,0.248896,0.0004815073,0.0002278265,0.0002690707,0.0006106509,0.003543322,0.006349132],"genre_scores_gemma":[0.9098302,0.0008966872,0.08324422,0.0001636753,0.00002084019,0.0001827924,0.0005257831,0.0001911619,0.004944679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001032668,"threshold_uncertainty_score":0.004186153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009520981312947513,"score_gpt":0.2616668957877692,"score_spread":0.2521459144748217,"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."}}