{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003064011,0.0001157263,0.00008635366,0.0000474216,0.0005137241,0.00004097721,0.0005193116,0.00003210832,0.00004283817],"category_scores_gemma":[0.00005350366,0.0001240491,0.00006325354,0.0002279355,0.0001153677,0.000007758699,0.0003258327,0.00008525475,0.000002607173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004449772,"about_ca_system_score_gemma":0.00009501108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001210721,"about_ca_topic_score_gemma":0.000001535299,"domain_scores_codex":[0.9986424,0.000007603432,0.0001421511,0.0003897539,0.0002211181,0.0005969711],"domain_scores_gemma":[0.9995162,0.00001023486,0.00003787473,0.0002627946,0.00003506989,0.0001378558],"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":[0.00002173345,0.00001736447,0.001386596,0.000006696393,0.000007195454,0.000001410358,0.0001057029,0.00175345,0.993588,0.0000728669,0.0006850119,0.002353965],"study_design_scores_gemma":[0.0003551026,0.0001306343,0.007138635,0.000002326195,0.00001048146,0.000008375418,0.0002171702,0.0006090697,0.8377717,0.0000575818,0.1534749,0.000224033],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8906209,0.002101754,0.1064223,0.00009882582,0.0003050358,0.000238012,0.00002375233,0.00001719601,0.0001722468],"genre_scores_gemma":[0.9965912,0.00008215642,0.002619775,0.0002555652,0.0001370142,0.00002955778,0.00005856466,0.00001724564,0.0002089014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1558163,"threshold_uncertainty_score":0.5058574,"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."}}