{"id":"W2790499753","doi":"10.1016/bs.mie.2018.01.027","title":"Brain Imaging Using Hyperpolarized 129 Xe Magnetic Resonance Imaging","year":2018,"lang":"en","type":"article","venue":"Methods in enzymology on CD-ROM/Methods in enzymology","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"NOSM University; Thunder Bay Regional Research Institute; Lakehead University","funders":"Canadian Institutes of Health Research","keywords":"Magnetic resonance imaging; Functional magnetic resonance spectroscopy of the brain; Nuclear magnetic resonance; Magnetic resonance spectroscopic imaging; Hyperpolarization (physics); Chemistry; Human brain; Medicine; Physics; Nuclear magnetic resonance spectroscopy; Neuroscience; Radiology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01122021,0.000895236,0.001819116,0.001315611,0.0004018405,0.00008357835,0.001448527,0.0004224514,0.001393999],"category_scores_gemma":[0.001293857,0.0009491051,0.0003350803,0.001627787,0.002196928,0.0003191763,0.000876867,0.002433617,0.0001121992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005910976,"about_ca_system_score_gemma":0.0005907532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002053841,"about_ca_topic_score_gemma":0.0001075433,"domain_scores_codex":[0.9801564,0.01355929,0.001575746,0.001965078,0.0003622422,0.002381305],"domain_scores_gemma":[0.9903551,0.00720865,0.0004258385,0.001495077,0.0002257638,0.0002895414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003962175,0.0004496622,0.1158629,0.00002023158,0.00004281826,0.0001799096,0.001369757,0.0000567371,0.2076427,0.0321836,0.0005109404,0.6412845],"study_design_scores_gemma":[0.01183992,0.0005431935,0.1143647,0.00035402,0.0001317312,0.0004974299,0.002770791,0.1690886,0.04244067,0.6178861,0.03677306,0.003309833],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2878099,0.002472327,0.6879297,0.001086724,0.002149901,0.0009197888,0.00004189755,0.0001430125,0.01744664],"genre_scores_gemma":[0.3053768,0.00001436575,0.6914512,0.001481378,0.0007499387,0.0001433417,0.00001773194,0.0001525012,0.0006127619],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6379747,"threshold_uncertainty_score":0.9998678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04952655676513269,"score_gpt":0.4390058776175245,"score_spread":0.3894793208523918,"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."}}