{"id":"W2621699596","doi":"10.1101/146878","title":"Unfolding the hippocampus: an intrinsic coordinate system for subfield segmentations and quantitative mapping","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Fondation Brain Canada; Ontario Brain Institute","keywords":"Hippocampal formation; Central sulcus; Neuroscience; Hippocampus; Grey matter; Neocortex; Computer science; Coordinate system; Anatomy; Artificial intelligence; Biology; Magnetic resonance imaging; White matter; Medicine; Radiology; Motor cortex","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":[0.0007522308,0.0005719938,0.0004317212,0.0008115654,0.0003910977,0.001084372,0.0005601403,0.0004267807,0.001834891],"category_scores_gemma":[0.002330058,0.0002407912,0.0005094594,0.0006494017,0.0006349797,0.0005810055,0.0008524363,0.0005900785,0.0004328053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005522936,"about_ca_system_score_gemma":0.0007073561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002457259,"about_ca_topic_score_gemma":0.002363042,"domain_scores_codex":[0.9996592,0.0001082831,0.00002113673,0.0001131511,0.00007221254,0.00002609428],"domain_scores_gemma":[0.999395,0.0001919815,0.0001033559,0.0001278632,0.0001505369,0.00003110452],"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":[0.0003631447,0.00009210371,0.005256732,0.0002528813,0.0001412585,0.0003292352,0.001028514,0.3217549,0.26425,0.03895198,0.003161045,0.3644182],"study_design_scores_gemma":[0.00001267001,0.00009174187,0.003481495,0.00001306096,0.00001422201,0.0001073531,0.0000873165,0.9496739,0.03410817,0.008613479,0.003760957,0.00003559561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03498595,0.00003575935,0.9636418,0.00005025617,0.000009969249,0.00003145923,0.0001373881,0.000836038,0.0002713599],"genre_scores_gemma":[0.2204043,0.00005896407,0.7782992,0.0000198572,0.000014555,0.0001023676,0.000278505,0.0003244152,0.0004977671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002457259,"threshold_uncertainty_score":0.006138325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07299884844012966,"score_gpt":0.331262584607385,"score_spread":0.2582637361672553,"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."}}