{"id":"W2052799151","doi":"10.1002/jmri.22688","title":"Dynamic phantom with heart, lung, and blood motion for initial validation of MRI techniques","year":2011,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; Foothills Medical Centre; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Imaging phantom; Artifact (error); Magnetic resonance imaging; Biomedical engineering; Match moving; Computer science; Digital subtraction angiography; Interventional magnetic resonance imaging; Computer vision; Motion (physics); Nuclear medicine; Medicine; Radiology; Angiography","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":[0.003023385,0.0008898269,0.0004846176,0.0008166381,0.0003554469,0.0006771393,0.0008073174,0.0009788787,0.002448295],"category_scores_gemma":[0.005369231,0.0003771511,0.0005326485,0.0003861508,0.000730116,0.0007644839,0.0006553056,0.0005835259,0.0007441932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003978507,"about_ca_system_score_gemma":0.0009933851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003283419,"about_ca_topic_score_gemma":0.0003342907,"domain_scores_codex":[0.9988392,0.0004262784,0.000117548,0.0001310331,0.0004276434,0.00005831268],"domain_scores_gemma":[0.9976168,0.001001212,0.0002901449,0.0004763063,0.0005032275,0.0001124053],"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":[0.0006383957,0.0005222569,0.00208531,0.0007803961,0.0000439924,0.0008468947,0.0004021543,0.01904173,0.9245635,0.006150342,0.001595722,0.0433293],"study_design_scores_gemma":[0.0003111011,0.005467389,0.006283625,0.0004008631,0.0002893629,0.008337134,0.0001639189,0.06280591,0.8098666,0.002513366,0.103378,0.0001828243],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1313575,0.002881526,0.8546323,0.0008895263,0.0004662239,0.002073505,0.000580827,0.001650908,0.005467828],"genre_scores_gemma":[0.4152443,0.002186038,0.5723366,0.0006261569,0.0001012879,0.002683358,0.001444142,0.0004317198,0.004946366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003023385,"threshold_uncertainty_score":0.01598936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01331771540831589,"score_gpt":0.3105560153007306,"score_spread":0.2972382998924147,"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."}}