{"id":"W4382371052","doi":"10.1101/2023.06.28.546942","title":"Endogenous tagging using split mNeonGreen in human iPSCs for live imaging studies","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"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; HEK 293 cells; Computational biology; Biology; Protein engineering; Cell culture; Cytokinesis; Cell biology; Cell; Genetics; Cell division; Gene; Embryonic stem cell; Biochemistry; Enzyme","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":[0.0007643962,0.00036002,0.0005104238,0.0004124856,0.0002975434,0.0006904971,0.0004696267,0.0006445926,0.001584833],"category_scores_gemma":[0.000237537,0.0002235412,0.0003725739,0.0003575481,0.0004488174,0.0003609776,0.0005661322,0.001167904,0.001361775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000533585,"about_ca_system_score_gemma":0.0003651793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001035594,"about_ca_topic_score_gemma":0.001093606,"domain_scores_codex":[0.9996777,0.00003183202,0.00003623217,0.00008215143,0.0001283233,0.00004381932],"domain_scores_gemma":[0.9997889,0.00004412935,0.00003146953,0.00006236966,0.00004516468,0.00002794658],"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":[0.00003080488,0.00001401644,0.0001138485,0.00003847211,0.000004607581,0.00007461393,0.00003187602,0.0002408808,0.9967153,0.0005381384,0.0001975061,0.001999946],"study_design_scores_gemma":[0.000006523105,0.00001762509,0.0005711609,0.00000663396,0.000008236875,0.0001420966,0.00001641457,0.001894505,0.9895746,0.000151035,0.007605692,0.000005477286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6154578,0.002264762,0.3574814,0.0007605885,0.0003690396,0.0004756789,0.008626183,0.003165822,0.01139869],"genre_scores_gemma":[0.8394378,0.001857342,0.1339333,0.0003198921,0.00002998499,0.000495474,0.006147015,0.001037066,0.01674215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001584833,"threshold_uncertainty_score":0.005301774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04403229658882326,"score_gpt":0.3124642501693806,"score_spread":0.2684319535805574,"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."}}