{"id":"W7119531590","doi":"10.1002/alz70856_107271","title":"Patient‐level predicting AD onset using lifespan volumetric trajectories","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroimaging; Dementia; Brain size; Healthy aging; Bayesian probability; Mri scan; Longitudinal data; Brain aging","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":[0.000770722,0.0003508024,0.0003936377,0.001777644,0.000212065,0.000861693,0.0003576076,0.0003941149,0.003470544],"category_scores_gemma":[0.004596787,0.0001724839,0.0003799818,0.001095083,0.0001308485,0.0004253612,0.0004807248,0.0004209938,0.001089842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003297947,"about_ca_system_score_gemma":0.0003319292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006175476,"about_ca_topic_score_gemma":0.006403038,"domain_scores_codex":[0.9997163,0.0000660107,0.000045938,0.0001040688,0.000039943,0.00002778047],"domain_scores_gemma":[0.9980622,0.0005641441,0.000509898,0.0002431948,0.0004543239,0.0001661833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007026413,0.00005194109,0.9645361,0.00007898769,0.0001775993,0.0001592135,0.00008831551,0.00587742,0.0009096227,0.0002160554,0.003272056,0.02392999],"study_design_scores_gemma":[0.00004061432,0.0003263113,0.9348705,0.0001141031,0.0002621386,0.001199768,0.0001829895,0.05045708,0.003658858,0.002862178,0.005968102,0.00005729525],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9383536,0.001035696,0.01052007,0.0003695767,0.00003396417,0.00006062384,0.04569368,0.0005746445,0.003358012],"genre_scores_gemma":[0.9793451,0.0002122559,0.004989346,0.00004065085,0.00001920543,0.00004180296,0.01474887,0.00003830002,0.0005645294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006175476,"threshold_uncertainty_score":0.01227909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04719402726807086,"score_gpt":0.3303723048348021,"score_spread":0.2831782775667312,"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."}}