{"id":"W4412056932","doi":"10.1016/j.cell.2026.04.031","title":"Image-based, pooled phenotyping reveals multidimensional, disease-specific variant effects","year":2025,"lang":"en","type":"preprint","venue":"Cell","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Institute of General Medical Sciences; National Human Genome Research Institute; National Heart, Lung, and Blood Institute; Novo Nordisk Fonden; Chan Zuckerberg Initiative; Alex's Lemonade Stand Foundation for Childhood Cancer; U.S. Department of Veterans Affairs","keywords":"PTEN; Phenotype; Biology; Computational biology; LMNA; Genetics; Subcellular localization; Genetic variants; Interactome; Genetic heterogeneity; Gene; Signal transduction; PI3K/AKT/mTOR pathway","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":[0.0006273866,0.000676057,0.0009857833,0.0009917666,0.0002676956,0.001210052,0.0005568638,0.0009131756,0.002335411],"category_scores_gemma":[0.0008187906,0.0005062529,0.0007588916,0.0007079436,0.0005077319,0.0005208232,0.00121776,0.001366989,0.0009993288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004570603,"about_ca_system_score_gemma":0.0002596734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008310759,"about_ca_topic_score_gemma":0.00167515,"domain_scores_codex":[0.9995052,0.00004430161,0.00002640949,0.0001896694,0.0001553928,0.00007898331],"domain_scores_gemma":[0.9991447,0.0002319428,0.0001542463,0.0002606828,0.00009893064,0.0001094626],"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":[0.00009339694,0.0000162968,0.0007262391,0.00004244107,0.00002768008,0.0001273834,0.0000209224,0.0005614167,0.9918947,0.0003213156,0.0003645885,0.005803624],"study_design_scores_gemma":[0.00002274678,0.00006705763,0.02023751,0.00001192828,0.00009284211,0.001280587,0.00004097212,0.01949294,0.9531413,0.001602029,0.003971393,0.0000387368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5886241,0.001511191,0.3963518,0.0008655729,0.0001961042,0.00005686437,0.004734403,0.004400594,0.003259347],"genre_scores_gemma":[0.7795704,0.001326041,0.2079174,0.000440694,0.00007555493,0.0000956836,0.004461161,0.00233732,0.003775656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002335411,"threshold_uncertainty_score":0.007812679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007759252596532634,"score_gpt":0.2627125969144212,"score_spread":0.2549533443178886,"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."}}