{"id":"W2168999235","doi":"10.1002/mrm.25705","title":"Motion robust GRAPPA for echo‐planar imaging","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Ghosting; Undersampling; Computer science; Single shot; Calibration; Computer vision; Artificial intelligence; Sensitivity (control systems); Interleaving; ENCODE; Physics; Optics; Chemistry","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":[0.0009393982,0.001084401,0.0004320518,0.0007307339,0.0002732401,0.0006329366,0.001172402,0.0008768167,0.001570898],"category_scores_gemma":[0.004500516,0.0004839715,0.0006490895,0.0006989397,0.0004105896,0.0008153675,0.0007000357,0.0009799107,0.0009147004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004491621,"about_ca_system_score_gemma":0.0009250856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009218301,"about_ca_topic_score_gemma":0.001256282,"domain_scores_codex":[0.999422,0.0002045292,0.00002946592,0.0001014926,0.0002133285,0.00002922432],"domain_scores_gemma":[0.9991533,0.000254309,0.0001428188,0.0001759327,0.0002434902,0.00003022279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006610762,0.0001270426,0.001919619,0.0008313282,0.0005183248,0.0006826236,0.0002317384,0.1029877,0.3503402,0.01980371,0.005155787,0.5167408],"study_design_scores_gemma":[0.0001042673,0.0006216899,0.004080266,0.0001175857,0.0002286003,0.002081818,0.00003935261,0.7773464,0.1803448,0.01079175,0.02412309,0.00012041],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008098045,0.0006780322,0.989622,0.0001175642,0.00003250338,0.00007224964,0.00005363124,0.0008607894,0.0004650815],"genre_scores_gemma":[0.08656174,0.0005401571,0.9110782,0.0001570935,0.0000423198,0.0001816951,0.0003152217,0.0003143153,0.0008092241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001570898,"threshold_uncertainty_score":0.005255222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05299651999868322,"score_gpt":0.3395754203288312,"score_spread":0.286578900330148,"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."}}