{"id":"W4413434252","doi":"10.1016/j.jneumeth.2025.110552","title":"Robust cortical thickness estimation in the presence of partial volumes using adaptive diffusion equation","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Montreal Neurological Institute and Hospital; National Institute on Aging; National Institutes of Health; McGill University; U.S. Department of Defense","keywords":"Diffusion; Estimation; Diffusion MRI; Diffusion equation; Computer science; Mathematics; Physics; Medicine; Magnetic resonance imaging; Thermodynamics; Economics","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":[0.001337629,0.0008114348,0.0006435792,0.00085706,0.0002677643,0.00114414,0.001025527,0.001010386,0.0007662636],"category_scores_gemma":[0.007870062,0.0007097384,0.000557946,0.0006758599,0.0005526693,0.001537683,0.001174454,0.001234402,0.0002392485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003105726,"about_ca_system_score_gemma":0.001162113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003775329,"about_ca_topic_score_gemma":0.004584712,"domain_scores_codex":[0.9996486,0.0001132786,0.00002856141,0.00007076836,0.0001102137,0.00002857623],"domain_scores_gemma":[0.9981588,0.001039656,0.0002676451,0.0002016609,0.0002812812,0.00005097375],"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":[0.0006337691,0.0001179916,0.007150994,0.0008092582,0.0005493782,0.001143234,0.0005850593,0.3575396,0.2774088,0.03591387,0.003165034,0.314983],"study_design_scores_gemma":[0.00003003875,0.00005713017,0.002667938,0.00003637473,0.00008903149,0.0007199104,0.0000458429,0.957625,0.02444016,0.01231389,0.001922717,0.00005193661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03111698,0.0003966017,0.9674644,0.0001756549,0.00003278748,0.0000302742,0.00008345306,0.0002991529,0.0004006299],"genre_scores_gemma":[0.3785444,0.00101783,0.6174285,0.000107469,0.00007111194,0.0001055873,0.0003819426,0.0004253633,0.001917805],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003775329,"threshold_uncertainty_score":0.007506728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2262721047221591,"score_gpt":0.4158717284346549,"score_spread":0.1895996237124958,"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."}}