{"id":"W4395037406","doi":"10.1101/2024.04.20.590404","title":"A scalable CRISPR-Cas9 gene editing system facilitates CRISPR screens in the malaria parasite <i>Plasmodium berghei</i>","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's & Women's Health Centre of British Columbia","funders":"Xiamen University; Umeå Universitet; Vetenskapsrådet; Japan Society for the Promotion of Science; Cancerfonden; Massachusetts Institute of Technology","keywords":"CRISPR; Plasmodium berghei; Genome editing; Biology; Malaria; Cas9; Computational biology; Parasite hosting; Gene; Subgenomic mRNA; Genetics; Virology; Computer science; World Wide Web; Immunology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003751433,0.0005707548,0.000536586,0.0003909157,0.0003861328,0.0005455691,0.0005692014,0.0004056061,0.002503675],"category_scores_gemma":[0.0002720257,0.0003610453,0.0003149117,0.0002371296,0.0003137038,0.0002852325,0.0007081841,0.00103668,0.001298924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003445745,"about_ca_system_score_gemma":0.0003539456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009781749,"about_ca_topic_score_gemma":0.002172287,"domain_scores_codex":[0.9996125,0.00004792818,0.00003451933,0.0001123534,0.0001433425,0.00004937277],"domain_scores_gemma":[0.9998199,0.00003362892,0.00004829107,0.00003038416,0.000018433,0.000049316],"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":[0.00002983303,0.00001673208,0.00009762823,0.00003120097,0.000005027922,0.00007474524,0.00001035191,0.0003065282,0.9966646,0.000224195,0.0003746331,0.00216463],"study_design_scores_gemma":[0.0000305539,0.0002118927,0.001579912,0.00001170435,0.00001686477,0.0004067239,0.00001823792,0.004649853,0.9820425,0.0001764733,0.01083051,0.00002468966],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5709346,0.0009691379,0.3962146,0.0008144076,0.0001803007,0.000690008,0.007601295,0.01417236,0.008423192],"genre_scores_gemma":[0.7680284,0.0006906963,0.2176852,0.0001724626,0.00003074899,0.00037071,0.00522435,0.001009226,0.006788137],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002503675,"threshold_uncertainty_score":0.008375585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008758645378082595,"score_gpt":0.2422302964584009,"score_spread":0.2334716510803183,"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."}}