{"id":"W4388125967","doi":"10.7554/elife.92819.1","title":"Endogenous tagging using split mNeonGreen in human iPSCs for live imaging studies","year":2023,"lang":"en","type":"preprint","venue":"","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Endogeny; Induced pluripotent stem cell; Computational biology; Computer science; Biology; Genetics; Gene; Biochemistry","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":[0.0006472748,0.0003496377,0.0005168661,0.0003843665,0.0002659806,0.0006365593,0.0004536287,0.0005988089,0.001453326],"category_scores_gemma":[0.0002174401,0.0002057408,0.0003669492,0.0003300652,0.0004272692,0.0003382621,0.0005207502,0.001100178,0.001223399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000485009,"about_ca_system_score_gemma":0.0003418358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000915223,"about_ca_topic_score_gemma":0.0009232616,"domain_scores_codex":[0.9997026,0.00002887337,0.00003461142,0.00007660782,0.0001136742,0.00004359254],"domain_scores_gemma":[0.9997861,0.00004478984,0.00003209327,0.00006421621,0.00004363769,0.00002928123],"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":[0.00002525381,0.00001232691,0.00009345706,0.00003320738,0.000003861468,0.00006792153,0.00002572548,0.0001840152,0.9972677,0.0004431227,0.0001236909,0.00171984],"study_design_scores_gemma":[0.000005390696,0.00001821832,0.0005123846,0.000005598401,0.000008038573,0.0001433253,0.00001428217,0.001531676,0.9913851,0.0001312941,0.006239827,0.000004735287],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6453311,0.002091065,0.3317948,0.0006052044,0.0003323455,0.0004214963,0.006418184,0.002815677,0.01019014],"genre_scores_gemma":[0.8629345,0.001719822,0.1150556,0.0002531119,0.00002621916,0.0003994489,0.004651536,0.0008657853,0.01409396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001453326,"threshold_uncertainty_score":0.004861891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0994170686717019,"score_gpt":0.4002061560582363,"score_spread":0.3007890873865344,"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."}}