{"id":"W2223567094","doi":"10.1002/0471142905.hg2104s88","title":"Efficient CRISPR/Cas9‐Based Genome Engineering in Human Pluripotent Stem Cells","year":2016,"lang":"en","type":"article","venue":"Current Protocols in Human Genetics","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institute for Health and Care Research; Canadian Institutes of Health Research; National Institutes of Health; Broad Institute; National Heart, Lung, and Blood Institute; Gladstone Institutes","keywords":"CRISPR; Genome editing; Induced pluripotent stem cell; Transcription activator-like effector nuclease; Biology; Zinc finger nuclease; Genome engineering; Computational biology; Cas9; Genome; Embryonic stem cell; Genetics; Gene","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":[0.0005722233,0.0004105064,0.0004088694,0.0005073739,0.000334711,0.0006231566,0.0006498692,0.0004983689,0.001495486],"category_scores_gemma":[0.0003858396,0.0003280631,0.0003980478,0.0004279985,0.0003873526,0.0003801115,0.0005686819,0.000991063,0.001449736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003318511,"about_ca_system_score_gemma":0.0004956637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005482291,"about_ca_topic_score_gemma":0.0008723343,"domain_scores_codex":[0.9992301,0.00009948351,0.00009805593,0.0001454076,0.000362159,0.00006483666],"domain_scores_gemma":[0.9998697,0.00002874729,0.00002525714,0.00003281929,0.00002565336,0.00001786448],"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":[0.00003296522,0.0000225159,0.0001446217,0.0001643999,0.00001083174,0.0001526694,0.00002897668,0.000848081,0.9729908,0.002687656,0.0008829024,0.02203361],"study_design_scores_gemma":[0.00001746516,0.0000930137,0.0005307659,0.00002098507,0.00001618717,0.0005052485,0.00001668399,0.003652383,0.9636376,0.0007346445,0.03075484,0.00002012253],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1827558,0.008624633,0.779205,0.0007778442,0.0006684494,0.001264165,0.003967227,0.005297461,0.01743943],"genre_scores_gemma":[0.5261933,0.0098518,0.4424485,0.0005292846,0.00008172465,0.0006858205,0.005678751,0.0004860323,0.01404471],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001495486,"threshold_uncertainty_score":0.005002856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02630001398569107,"score_gpt":0.3414671436948586,"score_spread":0.3151671297091675,"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."}}