{"id":"W4401878662","doi":"10.1371/journal.pone.0309204","title":"Advancing 7T perfusion imaging by pulsed arterial spin labeling: Using a parallel transmit coil for enhanced labeling robustness and temporal SNR","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Brain Institute; University Health Network","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Koninklijke Nederlandse Akademie van Wetenschappen","keywords":"Physics; Arterial spin labeling; Robustness (evolution); Electromagnetic coil; Nuclear magnetic resonance; Scanner; Computer science; Perfusion; Biomedical engineering; Optics; Chemistry; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00112057,0.0005889337,0.0003648931,0.0003030693,0.0002053508,0.0006138255,0.0003510169,0.0006683446,0.001620044],"category_scores_gemma":[0.001791705,0.0004018433,0.0001839206,0.0002900535,0.0005361647,0.0008863339,0.0005062456,0.0005467906,0.0006091415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002268997,"about_ca_system_score_gemma":0.0004784227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004458281,"about_ca_topic_score_gemma":0.0007819616,"domain_scores_codex":[0.9996979,0.0001132019,0.00001447132,0.00007272033,0.00007086667,0.00003081105],"domain_scores_gemma":[0.9993827,0.0002752466,0.0001102872,0.00007468137,0.0001190688,0.00003802515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002853925,0.00002894756,0.0004040205,0.0001569136,0.00001501388,0.0001307364,0.00007608336,0.0009314767,0.977629,0.000458818,0.00023561,0.01964802],"study_design_scores_gemma":[0.000072171,0.001115594,0.005522232,0.0000421091,0.0001367329,0.001908401,0.00006259631,0.03127551,0.9511269,0.0009432898,0.007746371,0.00004797228],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4751002,0.001112255,0.5180799,0.0005183755,0.0001161647,0.0001878455,0.0001447138,0.001346829,0.003393688],"genre_scores_gemma":[0.5818858,0.0009961871,0.4139943,0.0003503094,0.0001034162,0.0002238553,0.0002726342,0.0002673235,0.001906234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001620044,"threshold_uncertainty_score":0.005926192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0337636176972151,"score_gpt":0.3086517330126708,"score_spread":0.2748881153154558,"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."}}