{"id":"W4414705619","doi":"10.1038/s41592-025-02783-3","title":"HippoMaps: multiscale cartography of human hippocampal organization","year":2025,"lang":"en","type":"article","venue":"Nature Methods","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; HORIZON EUROPE Framework Programme; Hospital for Sick Children; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Canada Research Chairs; Canadian Institutes of Health Research; National Science Foundation; Savoy Foundation; Government of Canada; European Commission; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; McGill University","keywords":"Hippocampal formation; Hippocampus; Toolbox; Brain mapping; Neuroimaging; Functional magnetic resonance imaging; Human brain; Cognitive map; Cognition","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":[0.0005144716,0.0009578509,0.0006383135,0.001996475,0.0005034973,0.001780041,0.001239595,0.0007404957,0.01674689],"category_scores_gemma":[0.003548889,0.000738664,0.00125708,0.001467262,0.0004061427,0.001190434,0.002204978,0.0008441915,0.004811469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003166615,"about_ca_system_score_gemma":0.001219254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007483236,"about_ca_topic_score_gemma":0.01766377,"domain_scores_codex":[0.9997551,0.00003230486,0.00001714174,0.00008136093,0.00008548437,0.00002860071],"domain_scores_gemma":[0.9995102,0.0001848609,0.00007059773,0.0001097518,0.00007649139,0.00004806938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009966146,0.0001332006,0.01682903,0.002621193,0.001086828,0.001153662,0.002147073,0.07878502,0.04275466,0.02837195,0.4609924,0.3641284],"study_design_scores_gemma":[0.0003778212,0.0002268721,0.04072803,0.0005380822,0.0003348227,0.002702033,0.0007087622,0.4876874,0.04091181,0.1530533,0.2722827,0.0004484176],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05024985,0.001544589,0.6631225,0.001067884,0.0003757908,0.000290663,0.1421648,0.1346482,0.006535767],"genre_scores_gemma":[0.3056742,0.002321966,0.5153915,0.0004327483,0.0002770328,0.001124611,0.1420526,0.02702981,0.005695515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01674689,"threshold_uncertainty_score":0.05602401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02193017027897994,"score_gpt":0.3872990898282573,"score_spread":0.3653689195492774,"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."}}