{"id":"W170214809","doi":"10.1007/978-1-4939-0620-8_9","title":"A Tale of Two Methods: Combining Near-Infrared Spectroscopy with MRI for Studies of Brain Oxygenation and Metabolism","year":2014,"lang":"en","type":"article","venue":"Advances in experimental medicine and biology","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Oxygenation; Hypoxia (environmental); Cytochrome c oxidase; Near-infrared spectroscopy; Magnetic resonance imaging; Ischemia; Chemistry; Blood oxygenation; Metabolic rate; Biomedical engineering; Functional magnetic resonance imaging; Neuroscience; Nuclear magnetic resonance; Oxygen; Medicine; Cardiology; Internal medicine; Biology; Biochemistry; Radiology; Mitochondrion; Physics","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":[0.02556629,0.002333639,0.003816613,0.004331617,0.002432262,0.009849521,0.004188055,0.01143826,0.003447793],"category_scores_gemma":[0.02064614,0.001330873,0.002535122,0.001211052,0.0152814,0.01863833,0.008141306,0.01705638,0.002066438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002330311,"about_ca_system_score_gemma":0.003838986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003033144,"about_ca_topic_score_gemma":0.003729519,"domain_scores_codex":[0.9929976,0.002719152,0.0004098868,0.0009644331,0.00246248,0.0004464099],"domain_scores_gemma":[0.9875585,0.006619713,0.0005222081,0.001796232,0.002195295,0.001308148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001749706,0.0008874811,0.008867463,0.00313863,0.00180024,0.0008975751,0.002052592,0.00264413,0.04067368,0.1990058,0.1377236,0.6005591],"study_design_scores_gemma":[0.0004073911,0.001880712,0.009441046,0.002981247,0.0008587374,0.004455141,0.003072432,0.008937486,0.03407351,0.5106233,0.4214761,0.001792842],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008067308,0.270687,0.4596078,0.2274925,0.01700607,0.0006859694,0.0003400636,0.001786831,0.01432658],"genre_scores_gemma":[0.05552822,0.1082512,0.7211288,0.07358366,0.02064288,0.001037023,0.0003760431,0.001265737,0.01818647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02556629,"threshold_uncertainty_score":0.1352091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04257118788119178,"score_gpt":0.4758066527283675,"score_spread":0.4332354648471757,"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."}}