{"id":"W2953230159","doi":"10.1101/053058","title":"Continuous Genetic Recording with Self-Targeting CRISPR-Cas in Human Cells","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Naval Research; Natural Sciences and Engineering Research Council of Canada; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology; National Institutes of Health; National Science Foundation","keywords":"Biology; CRISPR; Cas9; Computational biology; DNA; Cell biology; Population; Genetics; Gene; Medicine","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":[0.0004716478,0.0001522967,0.0002472885,0.0001703037,0.0001339308,0.0004232696,0.0003678109,0.0003654175,0.002445845],"category_scores_gemma":[0.00072537,0.0001116848,0.000213522,0.0001565509,0.0001937225,0.0002055553,0.0002233897,0.0003138515,0.0008799956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002756891,"about_ca_system_score_gemma":0.0003117922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005069803,"about_ca_topic_score_gemma":0.0006373737,"domain_scores_codex":[0.9996796,0.00003967873,0.00003535038,0.00008416699,0.0001382166,0.00002301151],"domain_scores_gemma":[0.9996203,0.0001436827,0.0000829944,0.00005828897,0.00007225568,0.00002255149],"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":[0.0001399501,0.00001347612,0.0004107098,0.0001709207,0.000008581203,0.0001993542,0.00006915932,0.0004500639,0.972218,0.0009610964,0.001365301,0.02399336],"study_design_scores_gemma":[0.00001635382,0.0001799014,0.001080333,0.00001364353,0.00001507314,0.0005403811,0.0000237249,0.002844343,0.9765151,0.0002030844,0.01855295,0.00001527636],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6464741,0.004875637,0.31914,0.001896521,0.001325864,0.0004868871,0.00381879,0.004568092,0.01741412],"genre_scores_gemma":[0.8755161,0.001732314,0.101908,0.0004495066,0.0001259805,0.0002161849,0.001250479,0.0003054034,0.01849617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002445845,"threshold_uncertainty_score":0.008182168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005271597011996058,"score_gpt":0.2311468970891448,"score_spread":0.2258753000771488,"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."}}