{"id":"W4391328002","doi":"10.20944/preprints202401.1948.v1","title":"CRISPR/CAS Genome Editing Technology: Implications And Challenges","year":2024,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"CRISPR; Genome editing; Computational biology; Genome; Computer science; Biology; Genetics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01480849,0.001104601,0.001759583,0.001185762,0.001099699,0.004335749,0.003886802,0.007407104,0.004186769],"category_scores_gemma":[0.01259443,0.0006728191,0.0008778626,0.001346008,0.00771093,0.008265205,0.001992926,0.01102249,0.003687417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003018459,"about_ca_system_score_gemma":0.00285938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002358092,"about_ca_topic_score_gemma":0.001882105,"domain_scores_codex":[0.9945387,0.001720118,0.000318408,0.001026328,0.002063588,0.0003327275],"domain_scores_gemma":[0.985716,0.008350777,0.0006423214,0.00118268,0.002999845,0.001108418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002982354,0.000171664,0.001551411,0.003956918,0.0001449298,0.001030458,0.0006054985,0.004065989,0.01249161,0.2627567,0.1566111,0.5563154],"study_design_scores_gemma":[0.00005051561,0.0002363999,0.001386355,0.001556911,0.00004743991,0.002756554,0.001027861,0.002532212,0.006655504,0.3196709,0.6639102,0.0001690823],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004928986,0.4877205,0.04857889,0.4303347,0.007888604,0.00005382529,0.0004557929,0.0008903387,0.01914835],"genre_scores_gemma":[0.07789586,0.780215,0.05284642,0.06285574,0.01134009,0.0002357706,0.0007309131,0.0004311187,0.01344904],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01480849,"threshold_uncertainty_score":0.07831573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07024387818540614,"score_gpt":0.3698412558213853,"score_spread":0.2995973776359792,"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."}}