{"id":"W3038665043","doi":"10.1038/s41598-020-67581-7","title":"Author Correction: Multimodal hippocampal subfield grading for Alzheimer’s disease classification","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St Joseph's Health Care; University of British Columbia Hospital; Sunnybrook Health Science Centre; St Joseph's Health Centre; McGill University; Jewish General Hospital","funders":"","keywords":"Grading (engineering); Hippocampal formation; Computer science; Disease; Artificial intelligence; Alzheimer's disease; Neuroscience; Machine learning; Medicine; Psychology; Biology; Internal medicine","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":[0.005964119,0.001680459,0.001701856,0.004420911,0.002305612,0.003271772,0.003028975,0.004937432,0.08152208],"category_scores_gemma":[0.123274,0.0009910336,0.001773594,0.002432142,0.001766946,0.001748043,0.001713349,0.007182065,0.04166568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002219043,"about_ca_system_score_gemma":0.004672728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009236106,"about_ca_topic_score_gemma":0.01157033,"domain_scores_codex":[0.9931175,0.001143714,0.00187088,0.00100766,0.002346101,0.0005141811],"domain_scores_gemma":[0.9242246,0.01914358,0.003183965,0.006225494,0.044903,0.002319392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005659092,0.00000682062,0.0001930978,0.0001764858,0.00001998778,0.0002554844,0.00003850258,0.00004412638,0.0001159205,0.0006397025,0.9900545,0.008398817],"study_design_scores_gemma":[0.0001155889,0.00004196033,0.002300509,0.0007460781,0.00009863307,0.002470939,0.0001511057,0.0007411823,0.001168338,0.003467257,0.9886269,0.00007152739],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.0004071067,0.0006010418,0.001665377,0.03494419,0.9568109,0.00005657239,0.002154241,0.0007235406,0.00263699],"genre_scores_gemma":[0.06134295,0.006697896,0.0245079,0.0967971,0.5256016,0.0007528097,0.008134367,0.00530761,0.2708577],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08152208,"threshold_uncertainty_score":0.2727185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1274375025847921,"score_gpt":0.3218556701682777,"score_spread":0.1944181675834856,"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."}}