{"id":"W2597924261","doi":"10.1002/mrm.26679","title":"A pneumatic phantom for mimicking respiration‐induced artifacts in spinal MRI","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Université du Québec à Trois-Rivières; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Imaging phantom; Respiration; Nuclear magnetic resonance; Magnetic resonance imaging; Medicine; Biomedical engineering; Nuclear medicine; Anatomy; Radiology; 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":[0.0009996607,0.0005418866,0.0002380668,0.0004943308,0.0001786712,0.0003848409,0.0004924334,0.0006429291,0.001215678],"category_scores_gemma":[0.00317841,0.0003225328,0.0002556689,0.0002394838,0.0004562617,0.0004655165,0.0004755487,0.0003676938,0.0003450031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001675738,"about_ca_system_score_gemma":0.0005326366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000154626,"about_ca_topic_score_gemma":0.0001847192,"domain_scores_codex":[0.9995813,0.0001746755,0.00003347188,0.00004903123,0.0001422876,0.00001931175],"domain_scores_gemma":[0.9989849,0.0005517642,0.0001558659,0.000127077,0.0001122294,0.00006823504],"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":[0.0003032348,0.0001139434,0.0009780927,0.000391447,0.00001593749,0.0004718399,0.0001221342,0.005152169,0.966336,0.001441446,0.000499443,0.02417443],"study_design_scores_gemma":[0.0002115186,0.004580293,0.01123675,0.0001898056,0.00020743,0.008736687,0.00006828799,0.05560144,0.8831547,0.001283168,0.03461825,0.0001116949],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2501619,0.004165975,0.7365515,0.0007834752,0.00039362,0.001015642,0.0003812579,0.002209714,0.004336979],"genre_scores_gemma":[0.6602309,0.001492157,0.3343721,0.0003847289,0.00009081655,0.0006571543,0.0004853386,0.0001999357,0.002086774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001215678,"threshold_uncertainty_score":0.005286753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08425401067873506,"score_gpt":0.4090032089756248,"score_spread":0.3247491982968897,"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."}}