{"id":"W2058992833","doi":"10.1016/j.nicl.2014.02.002","title":"Longitudinal deformation models, spatial regularizations and learning strategies to quantify Alzheimer's disease progression","year":2014,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Alzheimer's disease research and treatments","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GE Healthcare; Biogen Idec; Genentech; National Institutes of Health; Servier; Alzheimer's Association; Instituo Cajal; Pfizer; BioClinica; F. Hoffmann-La Roche; Takeda Pharmaceutical Company; Elan; Novartis; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; General Electric; MetLife Foundation; Merck; Alzheimer's Drug Discovery Foundation; Marathon; Northern California Institute for Research and Education; Foundation for the National Institutes of Health","keywords":"Regularization (linguistics); Lasso (programming language); Spatial contextual awareness; Computer science; Pattern recognition (psychology); Context (archaeology); A priori and a posteriori; Artificial intelligence; Logistic regression; Piecewise; Machine learning; Mathematics; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003782713,0.0009538038,0.0007427046,0.001797908,0.0003237431,0.001130548,0.0007824744,0.001172402,0.0007520112],"category_scores_gemma":[0.004528804,0.0003751851,0.001089533,0.001074154,0.0009185816,0.001459642,0.001154576,0.001515407,0.0003432072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006575926,"about_ca_system_score_gemma":0.0009130016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003813708,"about_ca_topic_score_gemma":0.004143921,"domain_scores_codex":[0.999487,0.0001927438,0.00004786142,0.0001288791,0.00009249501,0.00005092383],"domain_scores_gemma":[0.9984965,0.0006172225,0.0003838316,0.0002344904,0.0001648434,0.0001030733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003995693,0.0002302502,0.02563803,0.0002007711,0.000402687,0.0001876618,0.0002207071,0.7445647,0.008864402,0.01310187,0.003700948,0.2024884],"study_design_scores_gemma":[0.000009388533,0.0000818551,0.004223692,0.00002885054,0.0000279191,0.0001086152,0.00003660514,0.9821808,0.001781366,0.01062426,0.000868724,0.00002792288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.207417,0.005256436,0.7825543,0.001910674,0.0001013668,0.00007136403,0.0007447985,0.0009279372,0.001016168],"genre_scores_gemma":[0.8342366,0.002030195,0.1587353,0.0002052377,0.0001686718,0.0001049866,0.001277928,0.0001775368,0.00306363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003813708,"threshold_uncertainty_score":0.02000517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1084473435734198,"score_gpt":0.4179780908566073,"score_spread":0.3095307472831875,"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."}}