{"id":"W4387502148","doi":"10.1016/j.euroneuro.2023.08.079","title":"ADVANCES IN PTSD GENOMICS 2023","year":2023,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Genome-wide association study; Imaging genetics; Genetics; Biology; Genetic association; Genomics; Candidate gene; Neuroimaging; Gene; Psychology; Single-nucleotide polymorphism; Computational biology; Neuroscience; Genotype; Genome","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009882296,0.0002252607,0.00018863,0.0001638155,0.0001195109,0.0000161428,0.0004687966,0.00003827879,0.002231559],"category_scores_gemma":[0.00007844057,0.0002479306,0.00005230794,0.0008741421,0.0002441855,0.0002710377,0.0004389043,0.0004689244,0.03067029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001531359,"about_ca_system_score_gemma":0.00001028551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001810774,"about_ca_topic_score_gemma":0.00003679989,"domain_scores_codex":[0.9967757,0.0009856125,0.0003969641,0.0008778578,0.0002164456,0.0007474361],"domain_scores_gemma":[0.9991678,0.0001794319,0.0001118333,0.0003317104,0.000003248798,0.0002059854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001971727,0.0002996479,0.05245814,0.00003355767,0.00001183413,0.004116803,0.001568788,0.0191333,0.579035,0.00002988077,0.03740434,0.3057116],"study_design_scores_gemma":[0.001041686,0.00008363659,0.4787389,0.00000566225,0.000006128613,0.0000181808,0.0000728512,0.0009761329,0.0001393054,0.00009051522,0.5185888,0.0002382041],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8403284,0.00008815161,0.0000507341,0.0008964291,0.0009346246,0.000373738,0.000007262967,0.0002991311,0.1570215],"genre_scores_gemma":[0.9862399,0.005244086,0.0001283416,0.006314554,0.0002169765,0.00003287508,0.00001031808,0.0001469183,0.001666063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5788957,"threshold_uncertainty_score":0.9999973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01869242375108288,"score_gpt":0.3026866206732526,"score_spread":0.2839941969221698,"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."}}