{"id":"W1983019361","doi":"10.1371/journal.pone.0060344","title":"aBEAT: A Toolbox for Consistent Analysis of Longitudinal Adult Brain MRI","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Key Research and Development Program of China; University of California, San Diego; National Institutes of Health; Genentech; IXICO; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Alzheimer's Association; Amorfix Life Sciences; F. Hoffmann-La Roche; Medpace; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; Synarc; Bayer HealthCare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Foundation for the National Institutes of Health","keywords":"Computer science; Segmentation; Toolbox; Image warping; Artificial intelligence; Image segmentation; Pattern recognition (psychology); Image processing; Computer vision; Image (mathematics)","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":[0.001968428,0.001975976,0.00112398,0.00227024,0.0004894758,0.001964336,0.002359838,0.001454909,0.03355754],"category_scores_gemma":[0.006588736,0.001329663,0.001970753,0.001071041,0.0005019478,0.001349632,0.002359644,0.002071083,0.0165725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004332107,"about_ca_system_score_gemma":0.001613861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001874642,"about_ca_topic_score_gemma":0.004412586,"domain_scores_codex":[0.9993643,0.0001221549,0.00008270873,0.0001534074,0.0002249569,0.00005250222],"domain_scores_gemma":[0.9984787,0.0007351829,0.0001591458,0.0002071571,0.0003231379,0.0000966189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007946956,0.0001370742,0.002223197,0.002441519,0.0006090377,0.0009454088,0.0004822021,0.02734591,0.06557552,0.01838319,0.2360667,0.6449955],"study_design_scores_gemma":[0.0003464605,0.0002665377,0.007525924,0.0006068284,0.0002453764,0.003455484,0.0002033503,0.4870123,0.08009918,0.07677176,0.3431252,0.0003417657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.001266205,0.0005047736,0.920219,0.0001490933,0.0001020385,0.000141521,0.004895988,0.07154551,0.001175919],"genre_scores_gemma":[0.01523243,0.0008197491,0.9485034,0.0003396784,0.00008501858,0.0010484,0.01071124,0.019568,0.003692084],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03355754,"threshold_uncertainty_score":0.1122611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04666778301999156,"score_gpt":0.2740358304337576,"score_spread":0.227368047413766,"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."}}