{"id":"W3163573529","doi":"10.1038/s42003-021-02133-x","title":"Integrating molecular, histopathological, neuroimaging and clinical neuroscience data with NeuroPM-box","year":2021,"lang":"en","type":"article","venue":"Communications Biology","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Health Canada; National Institutes of Health; Canada First Research Excellence Fund; Canada Research Chairs; Government of Canada; Ludmer Centre for Neuroinformatics and Mental Health; Weston Brain Institute; Biogen; Bristol-Myers Squibb; Fondation Brain Canada; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; National Institute on Aging; Alzheimer's Association; McGill University","keywords":"Neuroimaging; Neuroscience; Neurology; Toolbox; Molecular imaging; Precision medicine; Personalized medicine; Medicine; Bioinformatics; Computer science; Psychology; Pathology; Biology; In vivo","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":[0.00023356,0.0001021531,0.0002058025,0.00004459164,0.0002236796,0.00003104061,0.0006024034,0.00004394933,0.00001140354],"category_scores_gemma":[0.001107933,0.00007293226,0.00003106892,0.0002366428,0.001127515,0.0000750012,0.001585774,0.0003849755,0.000009511607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001246631,"about_ca_system_score_gemma":0.0002508554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001361839,"about_ca_topic_score_gemma":0.00001681258,"domain_scores_codex":[0.998467,0.0005573375,0.0002185314,0.0004738248,0.00007786267,0.0002054522],"domain_scores_gemma":[0.9965035,0.0003111374,0.00006253381,0.002794084,0.0001368801,0.0001919147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008951843,0.001225395,0.949719,0.00001574067,0.0002793897,0.001145805,0.00003044085,3.513393e-7,0.007708971,0.005626273,0.0002164812,0.03394261],"study_design_scores_gemma":[0.004335667,0.002593131,0.9218647,0.0001659382,0.001194043,0.004606196,0.0003192681,0.01671559,0.0005171196,0.001380155,0.0457618,0.0005463892],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.922258,0.03422587,0.004496194,0.02944648,0.0001344839,0.0006229788,0.0001233327,0.0001949867,0.008497735],"genre_scores_gemma":[0.97719,0.002974981,0.01769211,0.001714278,0.00001263612,0.00001282206,0.0003735597,0.00001092481,0.00001865081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05493209,"threshold_uncertainty_score":0.4154374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1947530579685791,"score_gpt":0.4591912815820978,"score_spread":0.2644382236135188,"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."}}