{"id":"W3149158769","doi":"10.1128/mbio.03338-20","title":"Cooperation between Different CRISPR-Cas Types Enables Adaptation in an RNA-Targeting System","year":2021,"lang":"en","type":"article","venue":"mBio","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Koneen Säätiö; Government of Canada; Jane ja Aatos Erkon Säätiö; Academy of Finland; Natural Sciences and Engineering Research Council of Canada; European Commission; U.S. Department of Agriculture","keywords":"CRISPR; Adaptation (eye); RNA; Computational biology; Computer science; Biology; Genetics; Gene; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000422382,0.000484761,0.000637832,0.0003377459,0.0003465412,0.0009385697,0.0005649102,0.0006953719,0.001209551],"category_scores_gemma":[0.0005881874,0.0003193259,0.0005406729,0.0001872744,0.0004303956,0.0005977221,0.001173426,0.000915872,0.0009387602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004241123,"about_ca_system_score_gemma":0.0003251759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003115165,"about_ca_topic_score_gemma":0.0004270041,"domain_scores_codex":[0.9993545,0.0000784266,0.00006517625,0.0002120331,0.0001762757,0.0001134815],"domain_scores_gemma":[0.9995025,0.0001337384,0.00009282287,0.000132288,0.00004276692,0.00009581799],"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":[0.00006364471,0.00001918049,0.0005018488,0.00003864022,0.0000112737,0.0001801301,0.00002544532,0.0002828936,0.9944413,0.001313425,0.000070558,0.003051634],"study_design_scores_gemma":[0.00001672141,0.0001180622,0.002822026,0.00001133685,0.00004718144,0.0008074346,0.00004604464,0.008891528,0.9803421,0.0009383992,0.005931451,0.00002769729],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.902514,0.001337241,0.08498713,0.0003101801,0.00012636,0.00008439957,0.0001891924,0.001330393,0.009121198],"genre_scores_gemma":[0.973581,0.0002893328,0.02295685,0.0001052617,0.00001198334,0.00003168395,0.0001385486,0.00007169566,0.002813692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001209551,"threshold_uncertainty_score":0.004046381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01419149672795512,"score_gpt":0.2870304109158798,"score_spread":0.2728389141879247,"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."}}