{"id":"W4387965927","doi":"10.1111/1755-0998.13881","title":"CRISPR‐based diagnostics detects invasive insect pests","year":2023,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Agriculture and Agri-Food Canada; Animal and Plant Health Inspection Service; Indian Agricultural Research Institute; National Institutes of Health; Indian Council of Agricultural Research; U.S. Department of Agriculture","keywords":"Biology; CRISPR; Computational biology; Identification (biology); Molecular diagnostics; Biotechnology; Gene; Genetics; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001738803,0.0002281485,0.00019917,0.0001666114,0.0001122675,0.00002802084,0.0002895975,0.000272066,0.00002850401],"category_scores_gemma":[0.0007697195,0.0002442351,0.0001297816,0.0002906166,0.0001036719,0.000001734653,0.0001905254,0.0001399363,0.000116001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000140421,"about_ca_system_score_gemma":0.00007446104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009406198,"about_ca_topic_score_gemma":0.0002026802,"domain_scores_codex":[0.9986103,0.00009898342,0.0002074769,0.0004566555,0.0001414893,0.000485109],"domain_scores_gemma":[0.9991944,0.0001167976,0.00005738911,0.0004340443,0.00006551447,0.0001317862],"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":[0.00005068733,0.00005882612,0.03055894,0.00006656497,0.0001143102,0.000399007,0.0001517037,0.01811835,0.9431318,0.00002108019,0.006386406,0.0009423241],"study_design_scores_gemma":[0.000764645,0.0005441004,0.07089303,0.00001771916,0.00004658793,0.00002984328,0.00008789125,0.0006779323,0.8926115,0.00008416015,0.03383891,0.0004036873],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945611,0.0009141827,0.003119145,0.0003045203,0.0002408431,0.0002282895,0.00001367895,0.0001049551,0.0005133156],"genre_scores_gemma":[0.9979002,0.0002048969,0.0003909117,0.0008827869,0.000139629,0.00008839553,0.000125872,0.00005509171,0.0002122508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0505203,"threshold_uncertainty_score":0.9959619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00859471678461473,"score_gpt":0.2688894441509841,"score_spread":0.2602947273663694,"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."}}