{"id":"W2395631589","doi":"10.1038/sdata.2015.59","title":"Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset","year":2015,"lang":"en","type":"article","venue":"Scientific Data","topic":"Neuroscience and Neuropharmacology Research","field":"Neuroscience","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Segmentation; Hippocampal formation; Computer science; Neuroimaging; Dentate gyrus; Artificial intelligence; Pattern recognition (psychology); Temporal lobe; Neuroscience; Biology; Epilepsy","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":[0.001981161,0.001520206,0.00131804,0.001939429,0.001525809,0.001368494,0.003099091,0.002075534,0.01073569],"category_scores_gemma":[0.003578009,0.0007853792,0.0009864612,0.001686966,0.0009271093,0.0005655923,0.001717952,0.001517957,0.00791125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007437143,"about_ca_system_score_gemma":0.002466872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005368335,"about_ca_topic_score_gemma":0.01177379,"domain_scores_codex":[0.9992045,0.0001278208,0.000157178,0.000295516,0.0001377636,0.00007718366],"domain_scores_gemma":[0.9984468,0.0002368265,0.0000900713,0.0006373537,0.0004984188,0.000090569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006417511,0.002344225,0.03021869,0.005533633,0.001004078,0.004807833,0.002083441,0.02725779,0.2159394,0.009011206,0.4115579,0.2838244],"study_design_scores_gemma":[0.002242238,0.002001181,0.100293,0.0009674769,0.001124125,0.01153228,0.0009579931,0.03967419,0.08988456,0.02468524,0.7259577,0.0006799783],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1818479,0.002322456,0.2693658,0.001409274,0.0007130664,0.01721423,0.4964682,0.01861457,0.01204451],"genre_scores_gemma":[0.0962052,0.0007393658,0.2509435,0.00076261,0.0001420585,0.0237544,0.6201954,0.002498292,0.004759059],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01073569,"threshold_uncertainty_score":0.03591448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3282191305563179,"score_gpt":0.4502045408260256,"score_spread":0.1219854102697077,"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."}}