{"id":"W4385498095","doi":"10.3390/s23156871","title":"The Objective Dementia Severity Scale Based on MRI with Contrastive Learning: A Whole Brain Neuroimaging Perspective","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; National Natural Science Foundation of China; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Neuroimaging; Dementia; Magnetic resonance imaging; Rating scale; Perspective (graphical); Medicine; Physical medicine and rehabilitation; Disease; Artificial intelligence; Psychology; Machine learning; Computer science; Radiology; Psychiatry; Pathology; Developmental psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00100409,0.001088951,0.0005909855,0.001627405,0.0001106824,0.0008651559,0.0005619413,0.0005641892,0.0005388152],"category_scores_gemma":[0.003145993,0.0001583891,0.0004639324,0.0008002472,0.0004625873,0.001000085,0.0005603141,0.000684563,0.0002303015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003393662,"about_ca_system_score_gemma":0.0003577723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00204046,"about_ca_topic_score_gemma":0.004219288,"domain_scores_codex":[0.9994447,0.0001430376,0.00006369405,0.0001450031,0.0001558056,0.00004774633],"domain_scores_gemma":[0.9991379,0.0002743585,0.0002082189,0.00007757389,0.0002388218,0.00006314211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001073759,0.0006957469,0.1238493,0.0008519203,0.00063318,0.0006611593,0.000369384,0.05995378,0.04661233,0.005805014,0.008255232,0.7512391],"study_design_scores_gemma":[0.00009354825,0.001467893,0.1446534,0.0002587173,0.0003826417,0.002150587,0.0003497302,0.7702391,0.05032509,0.02000311,0.009828703,0.0002474201],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4307469,0.008713241,0.5480857,0.001323175,0.0003204294,0.0003791747,0.002840143,0.000943607,0.006647584],"genre_scores_gemma":[0.899485,0.001781842,0.09495687,0.0002901436,0.0002176983,0.0001496077,0.001675173,0.0000367458,0.001406924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00204046,"threshold_uncertainty_score":0.005310178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009547967689511862,"score_gpt":0.2884167222718453,"score_spread":0.2788687545823335,"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."}}