{"id":"W3111088797","doi":"10.2967/jnumed.120.252130","title":"Quantitative Cerebral Blood Flow with PET in the 1980s: Going with the Flow (perspective on “Brain Blood Flow Measured with Intravenous H<sub>2</sub><sup>15</sup>O. I. Theory and Error Analysis” <i>J Nucl Med.</i> 1983;24:782–789 and “Brain Blood Flow Measured with Intravenous H<sub>2</sub><sup>15</sup>O. II. Implementation and Validation” <i>J Nucl Med.</i> 1983;24:790–798)","year":2020,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; National Institutes of Health; Medical Research Council Canada","keywords":"Cerebral blood flow; Blood flow; Perspective (graphical); Nuclear medicine; Cerebrovascular Circulation; Pet imaging; Flow (mathematics); Positron emission tomography; Medicine; Neuroscience; Medical physics; Psychology; Physics; Computer science; Mechanics; Radiology; Internal medicine; Artificial intelligence","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":[0.008834306,0.001145556,0.0009882739,0.002194949,0.000379435,0.001804113,0.000718548,0.002883052,0.0009301007],"category_scores_gemma":[0.01221932,0.000703508,0.0004949178,0.001778916,0.00850759,0.005375777,0.001349177,0.003791708,0.000404255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004870546,"about_ca_system_score_gemma":0.001815169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009089529,"about_ca_topic_score_gemma":0.008938141,"domain_scores_codex":[0.9981121,0.0007942815,0.0001657065,0.0003798644,0.0004773201,0.00007066518],"domain_scores_gemma":[0.9950177,0.003132854,0.00032409,0.0002566966,0.001152399,0.0001163864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008269851,0.0002367125,0.01229481,0.001867319,0.0002741033,0.0008487206,0.001916107,0.00705113,0.01814553,0.2367512,0.02820723,0.6915802],"study_design_scores_gemma":[0.0001368097,0.001341628,0.05121619,0.00262675,0.0002605623,0.004900194,0.001490101,0.01395859,0.05198696,0.2668211,0.6048388,0.0004223],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"commentary","genre_scores_codex":[0.03482562,0.7693576,0.1236431,0.05103726,0.003422885,0.00009647641,0.0005390552,0.0002354054,0.01684256],"genre_scores_gemma":[0.2717958,0.4736264,0.2067983,0.02253681,0.009991936,0.0003857179,0.0005216785,0.0003462654,0.01399707],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.009089529,"threshold_uncertainty_score":0.0467208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697637881071886,"score_gpt":0.2663161921444299,"score_spread":0.2493398133337111,"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."}}