{"id":"W4296462427","doi":"10.1101/2022.09.19.508444","title":"A multiplex platform to identify mechanisms and modulators of proteotoxicity in neurodegeneration","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"Medical Research Council; Irving Medical Center, Columbia University; Burroughs Wellcome Fund; National Institutes of Health; National Science Foundation","keywords":"Proteotoxicity; Neurodegeneration; Computational biology; Protein aggregation; Biology; Frontotemporal dementia; Chaperone (clinical); Protein folding; Cell biology; RNA; Chemistry; Genetics; Dementia; Gene; Medicine; Disease","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":[0.0005911562,0.0008756004,0.000495613,0.0006768684,0.0002012172,0.0006782435,0.0003628939,0.0007245547,0.002089295],"category_scores_gemma":[0.0002982128,0.0003622722,0.0004399859,0.0003164734,0.000233173,0.0004024917,0.000636638,0.0008417809,0.0009267445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004015873,"about_ca_system_score_gemma":0.0002427132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000303357,"about_ca_topic_score_gemma":0.0005637194,"domain_scores_codex":[0.9996465,0.00004546306,0.0000186887,0.00008001618,0.0001582573,0.00005100414],"domain_scores_gemma":[0.9997613,0.00004571716,0.00007110927,0.00003189431,0.00004344912,0.0000464302],"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":[0.00003720639,0.00003999627,0.0001132893,0.00002697322,0.000008682893,0.00002651141,0.000006747324,0.0001787289,0.9973789,0.0001173589,0.0000874299,0.001978172],"study_design_scores_gemma":[0.00001613319,0.0004433994,0.0006969825,0.000005888074,0.00001744179,0.0001142586,0.00001090923,0.002378227,0.9938449,0.00009755304,0.002364172,0.00001026105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8426336,0.005611924,0.140473,0.0006845758,0.0002834192,0.0005262457,0.003213726,0.002238836,0.004334569],"genre_scores_gemma":[0.8759814,0.002898171,0.1056898,0.0004310475,0.00007291814,0.0005766388,0.002203488,0.00009589297,0.01205068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002089295,"threshold_uncertainty_score":0.00698936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0174821820035672,"score_gpt":0.263758806233435,"score_spread":0.2462766242298678,"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."}}