{"id":"W4317936271","doi":"10.1002/cpz1.646","title":"Identifying Genetic Regulators of Protein‐Glycan Interactions with Genome‐Wide CRISPR Screening","year":2023,"lang":"en","type":"article","venue":"Current Protocols","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Glycan; Biology; Computational biology; Glycosylation; CRISPR; Immune system; Gene; Genetics; Glycoprotein","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":[0.002418267,0.001292225,0.001454992,0.001863765,0.001302938,0.001278789,0.001650356,0.001226483,0.0181141],"category_scores_gemma":[0.002127316,0.001192537,0.001321204,0.001187553,0.0007713556,0.0005348529,0.001570157,0.002489414,0.01034813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009584757,"about_ca_system_score_gemma":0.001850939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001977118,"about_ca_topic_score_gemma":0.005557067,"domain_scores_codex":[0.9977646,0.0003657542,0.0003179452,0.0004706263,0.0007617993,0.0003193211],"domain_scores_gemma":[0.9985077,0.0005709655,0.0001939491,0.0003197702,0.0002575618,0.0001501292],"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":[0.0003165523,0.0001680055,0.0007815774,0.000679545,0.00005678848,0.0003666051,0.0001710446,0.001405942,0.9646295,0.002964,0.01084756,0.01761284],"study_design_scores_gemma":[0.0002260042,0.0005563503,0.005017023,0.0001726543,0.0001294982,0.0008114093,0.0001190949,0.005583738,0.8742271,0.001328959,0.1116429,0.0001851342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1673188,0.003004618,0.5884699,0.001691841,0.0007596153,0.02306399,0.1503864,0.02551403,0.03979085],"genre_scores_gemma":[0.2353007,0.005064669,0.4675977,0.001735867,0.00009559117,0.03410105,0.1854673,0.005653,0.06498396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0181141,"threshold_uncertainty_score":0.06059766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03587425920216512,"score_gpt":0.3830464443491076,"score_spread":0.3471721851469424,"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."}}