{"id":"W4407856555","doi":"10.1016/j.jpsychires.2025.02.036","title":"Predicting mental health disorder onsets with Fibonacci sequencing: A genetic and epigenetic perspective","year":2025,"lang":"en","type":"article","venue":"Journal of Psychiatric Research","topic":"Genetics and Neurodevelopmental Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadians Living with HIV","funders":"","keywords":"Epigenetics; Fibonacci number; Perspective (graphical); Mental health; Psychology; Genetics; Computational biology; Biology; Psychiatry; Computer science; Artificial intelligence; Gene; Mathematics","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":[0.0007316543,0.0006284047,0.0003612067,0.001479759,0.0004686183,0.0009518965,0.0006656192,0.001077276,0.003105515],"category_scores_gemma":[0.002665664,0.0002025869,0.0004196103,0.0007458559,0.0004143181,0.0006310822,0.0005333224,0.0007855143,0.0004475543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003007849,"about_ca_system_score_gemma":0.0004689646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003842279,"about_ca_topic_score_gemma":0.007463091,"domain_scores_codex":[0.9996982,0.00006698137,0.0000247597,0.0000946718,0.00005806514,0.00005734648],"domain_scores_gemma":[0.9992187,0.0003657829,0.0001717743,0.00003577975,0.0001130728,0.00009487851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003358129,0.00006105944,0.9524378,0.00004980562,0.0001476842,0.003372625,0.0001746836,0.0006525256,0.01188898,0.001004151,0.001269614,0.02860526],"study_design_scores_gemma":[0.00002227367,0.0001732745,0.9683329,0.0001873998,0.0003073967,0.0116278,0.0006925125,0.004278009,0.004975797,0.005421111,0.003937609,0.00004399722],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9735685,0.004463112,0.006605806,0.003484116,0.00017579,0.00004765917,0.001659738,0.00008832121,0.00990682],"genre_scores_gemma":[0.9930495,0.001334969,0.00392939,0.0004574793,0.0001472345,0.00001311005,0.0003946801,0.00002108054,0.0006524904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003842279,"threshold_uncertainty_score":0.01038903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792571037602909,"score_gpt":0.3462163848773639,"score_spread":0.3282906745013349,"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."}}