{"id":"W2975488016","doi":"10.1534/g3.119.400535","title":"Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning","year":2019,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"National Science Foundation; National Cancer Institute; National Human Genome Research Institute; National Institute of General Medical Sciences; Canadian Institute for Advanced Research; Alzheimer's Association","keywords":"Mutagenesis; Alanine scanning; Context (archaeology); Alanine; Amino acid; Saturated mutagenesis; Protein aggregation; Computational biology; In vitro; Fibril; Biochemistry; Biology; Yeast; Mutation; Chemistry; Genetics; Gene","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":[0.0003236262,0.0004233576,0.0002724482,0.0002225697,0.0001334379,0.0002892085,0.0002033145,0.0002601301,0.0006513501],"category_scores_gemma":[0.0003906984,0.00014643,0.000286578,0.0002005294,0.0002462932,0.00021534,0.0002968821,0.0005654931,0.0002263081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002163131,"about_ca_system_score_gemma":0.0001704164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008235266,"about_ca_topic_score_gemma":0.001031954,"domain_scores_codex":[0.9998844,0.00003162013,0.00001304554,0.00002546391,0.00002832664,0.00001713982],"domain_scores_gemma":[0.9997502,0.00009429476,0.00006708568,0.00003032142,0.0000331114,0.00002497614],"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":[0.00004708741,0.00002451215,0.0006836226,0.000020779,0.00001256332,0.00005226322,0.00001686707,0.0006346298,0.9972906,0.0001267235,0.00001930843,0.00107102],"study_design_scores_gemma":[0.0000166775,0.0003874313,0.007526438,0.000007623706,0.00005818022,0.000500136,0.00005381181,0.01340771,0.9764098,0.0004309748,0.001188123,0.00001304833],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855433,0.0002935866,0.01331605,0.00003999331,0.000008670384,0.0000331977,0.0002144686,0.00005803082,0.0004927034],"genre_scores_gemma":[0.9900625,0.0002267257,0.009214036,0.00003683096,0.000003347303,0.00001066173,0.0002019161,0.0000237503,0.0002201692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008235266,"threshold_uncertainty_score":0.002179027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588008224355731,"score_gpt":0.2934282318209867,"score_spread":0.2775481495774294,"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."}}