{"id":"W2302620309","doi":"10.1016/j.neurobiolaging.2016.03.009","title":"Mutation analysis of the MS4A and TREM gene clusters in a case-control Alzheimer's disease data set","year":2016,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Occupational Cancer Research Centre; University of Toronto","funders":"National Institute on Aging; Alzheimer Society; National Institute for Health and Care Research; Canadian Institutes of Health Research; National Institutes of Health; Wellcome Trust","keywords":"TREM2; Missense mutation; Gene; Genetics; Locus (genetics); Biology; Gene isoform; Gene cluster; Coding region; Mutation; Alzheimer's disease; Disease; Medicine; Receptor; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001982189,0.00009943472,0.000199919,0.0002559296,0.0000645705,0.000008107152,0.0002654401,0.00002831369,0.00001726508],"category_scores_gemma":[0.0002937314,0.00006347576,0.00005151297,0.0004294594,0.0001559402,0.0001543759,0.0001359053,0.0000611842,0.000001082167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004949221,"about_ca_system_score_gemma":0.00002692022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009212449,"about_ca_topic_score_gemma":0.00006217149,"domain_scores_codex":[0.998476,0.0005555635,0.0003248861,0.0004218557,0.00008930724,0.0001324003],"domain_scores_gemma":[0.9986479,0.0005242444,0.0002312577,0.0005306697,0.00002052966,0.00004540474],"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":[0.00004607361,0.00002044277,0.009055601,0.000005530006,0.00002870597,0.00009479251,0.0001024457,0.001392834,0.9880706,0.0002337165,0.0000176372,0.0009316173],"study_design_scores_gemma":[0.001395186,0.00006111721,0.07139902,0.00001670855,0.0006295103,0.0001643551,0.00001946475,0.04109616,0.8849695,0.00008506824,0.00002437139,0.0001395079],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996816,0.00001985256,0.0005880162,0.001917374,0.000135786,0.0001970883,0.0003005415,0.00001658465,0.000008689316],"genre_scores_gemma":[0.9989845,0.00002635452,0.00003733393,0.0009073715,0.00001073311,0.000004179655,0.000006799011,0.000007925428,0.00001479024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1031011,"threshold_uncertainty_score":0.2588466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05692283259361416,"score_gpt":0.2869493483988539,"score_spread":0.2300265158052398,"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."}}