{"id":"W4403548360","doi":"10.1039/d4cc04534c","title":"CRISPR/Cas12a assay for amol level microRNA by combining enzyme-free amplification and single particle analysis","year":2024,"lang":"en","type":"article","venue":"Chemical Communications","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Outstanding Youth Science and Technology Talents Program of Sichuan; Fundamental Research Funds for the Central Universities; Sichuan Province Science and Technology Support Program; Chengdu Science and Technology Bureau; National Natural Science Foundation of China","keywords":"CRISPR; Chemistry; Molecular biology; Computational biology; Biology; Biochemistry; Gene","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":[0.000172913,0.0001060353,0.0001200908,0.0000335796,0.00009797281,0.00007511184,0.0004014857,0.0000954718,0.000004134634],"category_scores_gemma":[0.0001893431,0.0001137994,0.00009552656,0.0002086384,0.00009887555,0.000005268826,0.0002551667,0.00009529274,0.000002598343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001699126,"about_ca_system_score_gemma":0.00001606103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001315973,"about_ca_topic_score_gemma":0.00001928271,"domain_scores_codex":[0.9993081,0.00002732266,0.0001980167,0.0002509921,0.00005572522,0.000159856],"domain_scores_gemma":[0.9987139,0.0001264774,0.00002815504,0.0009966625,0.00005874141,0.00007603774],"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":[0.000005373854,0.00005423721,0.0001517374,0.00002169516,0.0001555539,5.978499e-8,0.00007742141,0.00001812184,0.9897178,0.0004312358,0.007476218,0.001890565],"study_design_scores_gemma":[0.0001998122,0.00002962015,0.0001289321,0.00001091671,0.0002124248,0.000002803628,0.00006706036,0.009607929,0.9334978,0.0002237039,0.05586942,0.0001495126],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3973984,0.02307316,0.5742087,0.003867951,0.00006721656,0.0003390592,0.0004034254,0.00009485726,0.00054722],"genre_scores_gemma":[0.9878722,0.0002504154,0.01051537,0.00008814839,0.00003543173,0.00009217002,0.0008514359,0.0000203126,0.0002745544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5904738,"threshold_uncertainty_score":0.4640606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03950702468401947,"score_gpt":0.3368679160143708,"score_spread":0.2973608913303513,"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."}}