{"id":"W4407103926","doi":"10.7554/elife.103530.1","title":"Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Robarts Clinical Trials","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Zona incerta; Zona; Diffusion; Diffusion MRI; Cartography; Geography; Geology; Biology; Neuroscience; Physics; Magnetic resonance imaging; Medicine; Radiology; Virology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004359872,0.0002307154,0.0001516168,0.00163869,0.0002340463,0.0008762926,0.0003168278,0.0003459617,0.001754327],"category_scores_gemma":[0.001684914,0.0002712937,0.0001405667,0.0006718279,0.000426642,0.0004664402,0.000364701,0.0003436304,0.0005527952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004168824,"about_ca_system_score_gemma":0.0004886083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007729732,"about_ca_topic_score_gemma":0.01164413,"domain_scores_codex":[0.9998796,0.00001930492,0.000005964153,0.00005062659,0.00003114823,0.00001341497],"domain_scores_gemma":[0.9997349,0.00008173733,0.00006929168,0.00004572381,0.00005110905,0.00001727287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009251678,0.00008637857,0.05379802,0.0006876958,0.0003108129,0.0009702044,0.001375203,0.01133139,0.6677947,0.01226287,0.006553956,0.2439035],"study_design_scores_gemma":[0.0001283621,0.0002880754,0.58882,0.00037425,0.000362644,0.009597113,0.001134698,0.08877723,0.2393063,0.02435221,0.04661472,0.0002444327],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8234101,0.005375781,0.1568573,0.001468982,0.0000560427,0.0001832218,0.003681545,0.0009947391,0.007972251],"genre_scores_gemma":[0.9440377,0.001292454,0.05105331,0.0001273676,0.00002522325,0.00007087513,0.0006581462,0.0001472178,0.002587736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007729732,"threshold_uncertainty_score":0.01536947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08933693897071142,"score_gpt":0.3609058517935722,"score_spread":0.2715689128228608,"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."}}