{"id":"W4403489647","doi":"10.51731/cjht.2024.999","title":"CRISPR Technologies for In Vivo and Ex Vivo Gene Editing","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CRISPR; Ex vivo; Genome editing; Biology; In vivo; Gene; Genetics; Computational biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002282276,0.001016547,0.001517944,0.001290652,0.0005802531,0.003140032,0.001697452,0.002085799,0.009308706],"category_scores_gemma":[0.002055811,0.0009740498,0.001017348,0.0008917825,0.001712644,0.002147191,0.00155864,0.004821293,0.007409303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000978398,"about_ca_system_score_gemma":0.0007652249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004651173,"about_ca_topic_score_gemma":0.0005389942,"domain_scores_codex":[0.9968508,0.0008173882,0.000240076,0.0004885786,0.001369929,0.0002332766],"domain_scores_gemma":[0.9986078,0.0005564678,0.0002412616,0.0002519573,0.000190616,0.0001519008],"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":[0.0002933624,0.0002041222,0.0008228662,0.004144341,0.0002005597,0.0008275855,0.0004617383,0.00274005,0.3644682,0.08556591,0.09560968,0.4446616],"study_design_scores_gemma":[0.00006379985,0.0003464749,0.0006291003,0.0004614622,0.00008050664,0.002620422,0.0001009503,0.002055759,0.150272,0.01943495,0.8238006,0.0001339199],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01161772,0.1496053,0.7394384,0.01661674,0.006931173,0.000808114,0.003113553,0.0154885,0.05638056],"genre_scores_gemma":[0.1408819,0.2504755,0.5124496,0.01255061,0.003337055,0.00191323,0.005902866,0.002702815,0.06978641],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.009308706,"threshold_uncertainty_score":0.03114069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01112360229774007,"score_gpt":0.3030946579556271,"score_spread":0.2919710556578871,"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."}}