{"id":"W604748745","doi":"","title":"Characterization of the Hemodynamic Profile of Early Alzheimer's Disease via Arterial Spin Labeling Magnetic Resonance Imaging","year":2012,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Sunnybrook Research Institute; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Cerebral blood flow; Arterial spin labeling; Hemodynamics; Cardiology; Magnetic resonance imaging; Medicine; Alzheimer's disease; Perfusion; Internal medicine; Dementia; Neurocognitive; Vascular dementia; Blood flow; Perfusion scanning; Pathology; Disease; Radiology; Cognition; Psychiatry","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":[0.0001449121,0.0001234393,0.00009850135,0.0002421162,0.00007763207,0.000162488,0.00005777719,0.0001224125,0.0005169661],"category_scores_gemma":[0.0002237551,0.00004910432,0.00004578368,0.0001402399,0.00009236369,0.00009445586,0.00004155384,0.0001711999,0.0001231335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001057069,"about_ca_system_score_gemma":0.0001608052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001253234,"about_ca_topic_score_gemma":0.001683601,"domain_scores_codex":[0.9999816,0.000003601219,0.000001009149,0.000004034959,0.000004990879,0.000004771317],"domain_scores_gemma":[0.9999514,0.00001337299,0.00001006966,0.000003522316,0.00001253753,0.00000918086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001180762,0.0003088133,0.04338494,0.0001205465,0.00002622043,0.000409082,0.0004085811,0.0002982485,0.8830025,0.0002069746,0.0003577998,0.0702956],"study_design_scores_gemma":[0.0000491639,0.001896144,0.9028616,0.00002017577,0.00005642219,0.001277455,0.0002500485,0.002280317,0.08835437,0.000424682,0.002513479,0.00001623317],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958669,0.001302067,0.002031985,0.00003168673,0.000005162989,0.00001459108,0.0001120757,0.00001251374,0.0006231549],"genre_scores_gemma":[0.9945479,0.001307831,0.002800705,0.0000198842,0.00001796511,0.00002341721,0.0002142866,0.000003521686,0.001064475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001253234,"threshold_uncertainty_score":0.002491891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008511001937134522,"score_gpt":0.259282310280586,"score_spread":0.2507713083434515,"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."}}