{"id":"W4310102492","doi":"10.1021/acscentsci.2c00836","title":"nuPRISM: Microfluidic Genome-Wide Phenotypic Screening Platform for Cellular Nuclei","year":2022,"lang":"en","type":"article","venue":"ACS Central Science","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"CRISPR; Biology; Phenotype; Computational biology; Cas9; Genetic screen; Genome; Context (archaeology); Subcellular localization; Function (biology); Cell biology; Genetics; Gene; Cytoplasm","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":[0.0003944,0.0004262162,0.0004054897,0.0003707153,0.000318628,0.0004304328,0.0007709908,0.0005687017,0.003079202],"category_scores_gemma":[0.000371677,0.000362112,0.0002708887,0.0001289312,0.0002939729,0.0003101382,0.0008798657,0.0006989657,0.001053805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004954273,"about_ca_system_score_gemma":0.0004679474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005987767,"about_ca_topic_score_gemma":0.001782323,"domain_scores_codex":[0.9996606,0.00003201322,0.00001306334,0.00009836667,0.0001475227,0.00004832088],"domain_scores_gemma":[0.9997838,0.00006128861,0.00004775861,0.00003703573,0.00002755852,0.00004257132],"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":[0.00004788037,0.00002685863,0.0002569255,0.00006780356,0.00001172973,0.0001019103,0.00002610704,0.00049555,0.9881482,0.0009019234,0.002009346,0.007905809],"study_design_scores_gemma":[0.0000245595,0.0001149119,0.002261385,0.00001208201,0.00001276185,0.0003942888,0.00001970527,0.01117493,0.971792,0.0003604319,0.01379837,0.00003452018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5687996,0.002377076,0.3676602,0.001576548,0.0005000624,0.0006156571,0.01197902,0.02643203,0.02005976],"genre_scores_gemma":[0.8081058,0.001248974,0.1703369,0.0007682797,0.00005243661,0.001110298,0.004534526,0.0007885361,0.01305429],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003079202,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012662737711937,"score_gpt":0.2513998938543803,"score_spread":0.241273266477261,"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."}}