{"id":"W2759801681","doi":"10.1142/s2529732517400090","title":"CRISPR System: From Adaptive Immunity to Genome Editing","year":2017,"lang":"en","type":"article","venue":"Molecular Frontiers Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of California, San Francisco; Connaught Fund","keywords":"CRISPR; Genome editing; Cas9; Computational biology; DNA; Genome; Biology; Acquired immune system; Function (biology); Förster resonance energy transfer; Computer science; Genetics; Gene; Antigen; Physics","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":[0.0006791986,0.0005744764,0.0009464163,0.0006605866,0.0004887147,0.001356323,0.001029185,0.001032295,0.006552798],"category_scores_gemma":[0.0006204492,0.0004727075,0.0005542049,0.0004155344,0.0006814497,0.0007414653,0.001369205,0.002400926,0.005852685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005565062,"about_ca_system_score_gemma":0.0004254131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003353687,"about_ca_topic_score_gemma":0.0003399505,"domain_scores_codex":[0.9992556,0.0001262606,0.00005633256,0.0002241553,0.0002327432,0.0001049112],"domain_scores_gemma":[0.9997244,0.00005588714,0.00003782934,0.00007373811,0.00003265556,0.00007542681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003523644,0.00008322175,0.0005370456,0.0005947554,0.00009531944,0.0003145486,0.000134646,0.001072244,0.8484246,0.01719529,0.02234363,0.1088524],"study_design_scores_gemma":[0.00009185047,0.0005182813,0.001232774,0.00009225878,0.00008856311,0.001945756,0.0000460236,0.006677592,0.6989623,0.00962046,0.2806014,0.0001228781],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.08280378,0.01638534,0.786065,0.005971877,0.003312496,0.0005829904,0.006992126,0.05317813,0.04470813],"genre_scores_gemma":[0.473864,0.01447503,0.4297522,0.003968481,0.0008770615,0.000828256,0.008938289,0.004350023,0.06294677],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.006552798,"threshold_uncertainty_score":0.02192128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007380483039579626,"score_gpt":0.2692351209038998,"score_spread":0.2618546378643202,"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."}}