{"id":"W2901779940","doi":"10.1007/s00429-018-1798-7","title":"A population-based atlas of the human pyramidal tract in 410 healthy participants","year":2018,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Région Normandie","keywords":"Tractography; Pyramidal tracts; Diffusion MRI; Atlas (anatomy); Population; Corticospinal tract; Human brain; Artificial intelligence; Neuroscience; Psychology; Magnetic resonance imaging; Computer science; Anatomy; Medicine; Radiology","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":[0.0002072439,0.0001961189,0.0001694985,0.0007162559,0.0004082317,0.0003812639,0.0002661366,0.0003921905,0.006143799],"category_scores_gemma":[0.0006135193,0.0002090024,0.0001501808,0.0008703268,0.0002541894,0.0002093838,0.0002420507,0.0001438206,0.0009870538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002583845,"about_ca_system_score_gemma":0.0005807182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02058177,"about_ca_topic_score_gemma":0.05104241,"domain_scores_codex":[0.9999329,0.00001186575,0.000005316782,0.00002828968,0.00001143702,0.00001016459],"domain_scores_gemma":[0.9998739,0.00003018915,0.00001689071,0.00002952623,0.00003850896,0.00001099481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002495714,0.0003952057,0.4956232,0.0006850712,0.0004794373,0.007608616,0.009393536,0.01488386,0.1124779,0.008087458,0.06134764,0.2865224],"study_design_scores_gemma":[0.00005699274,0.0002484127,0.9441519,0.00003833441,0.0001069504,0.01237202,0.00149403,0.005944123,0.003416557,0.004679568,0.02742369,0.00006751223],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9478482,0.0002652466,0.01881003,0.0001487798,0.00001703701,0.0001375049,0.02356248,0.0004371422,0.008773571],"genre_scores_gemma":[0.9781697,0.0002184648,0.01013633,0.00003545034,0.000008071961,0.0001315658,0.007069862,0.00006609379,0.004164537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02058177,"threshold_uncertainty_score":0.04092395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0587474499733975,"score_gpt":0.3642715730419366,"score_spread":0.3055241230685391,"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."}}