{"id":"W4396495846","doi":"10.1021/acs.analchem.3c05776","title":"Detection of sgRNA via SHERLOCK as Potential CRISPR Related Gene Doping Control Strategy","year":2024,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Sporthochschule Köln; Manfred Donike Institut für Dopinganalytik; World Anti-Doping Agency","keywords":"CRISPR; Subgenomic mRNA; Recombinase Polymerase Amplification; Nucleic acid; Computational biology; Chemistry; Genome editing; Guide RNA; Polymerase chain reaction; Gene; Biology; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009945537,0.0007153814,0.0005002667,0.0005710698,0.0002374953,0.0006140847,0.0006464469,0.0009671868,0.0009066276],"category_scores_gemma":[0.001279544,0.0003512756,0.0003180529,0.0003515425,0.000635929,0.0004754392,0.0005313838,0.0009856016,0.0007618099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003708979,"about_ca_system_score_gemma":0.0003862968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002198502,"about_ca_topic_score_gemma":0.0006481879,"domain_scores_codex":[0.9988299,0.0002246058,0.00006544765,0.0003708527,0.0004187541,0.00009033248],"domain_scores_gemma":[0.9991094,0.0002674908,0.0003188915,0.00008653408,0.0001494214,0.00006815283],"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":[0.00005076304,0.00002269586,0.0002600152,0.00008667806,0.000007663838,0.00005521053,0.0000406286,0.0001594451,0.9929855,0.0003448158,0.0001200624,0.005866435],"study_design_scores_gemma":[0.000002393311,0.0000719413,0.0001965745,0.000004413349,0.000005411764,0.0000929555,0.00001084977,0.001270608,0.9970732,0.00005812027,0.001206025,0.000007500174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4759963,0.003928396,0.5088733,0.0007103349,0.0002314746,0.0002863254,0.0008152395,0.003020133,0.006138464],"genre_scores_gemma":[0.7057965,0.002062331,0.2813187,0.0005756256,0.00004306591,0.000303375,0.0007662214,0.0001983527,0.008935732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009945537,"threshold_uncertainty_score":0.005259752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003576248903292293,"score_gpt":0.2693188970110328,"score_spread":0.2657426481077405,"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."}}