{"id":"W2466576521","doi":"10.1002/cmr.b.21323","title":"Accuracy of the Magnetic Field Gradient Waveform Monitor Technique and Consequent Accuracy of Pre‐Equalized Gradient Waveform","year":2016,"lang":"en","type":"article","venue":"Concepts in Magnetic Resonance Part B","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Saudi Aramco","keywords":"Waveform; Computer science; Physics; Telecommunications","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":[0.003541685,0.0004967362,0.0003820107,0.0007173978,0.000289941,0.001235478,0.001005155,0.0007847403,0.001183245],"category_scores_gemma":[0.02012653,0.0003005668,0.0002263698,0.0004931594,0.0007021269,0.001290744,0.0009204789,0.0007341254,0.0004506233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005359869,"about_ca_system_score_gemma":0.0006399344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007331951,"about_ca_topic_score_gemma":0.0005768083,"domain_scores_codex":[0.996438,0.0009596257,0.000206232,0.0005618628,0.001686853,0.0001474692],"domain_scores_gemma":[0.9908975,0.004317584,0.0008435709,0.001990146,0.001870967,0.00008025051],"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":[0.001645494,0.0000918714,0.0119642,0.0006751093,0.00008399383,0.0003287742,0.0003988949,0.06151107,0.5437976,0.01565227,0.001374492,0.3624762],"study_design_scores_gemma":[0.00003978083,0.0004630127,0.009651487,0.00008982908,0.00006001229,0.001100126,0.00006733523,0.2208355,0.7572135,0.004888166,0.005488765,0.0001023688],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1081677,0.0009070942,0.8858901,0.000332264,0.0001842271,0.00008254709,0.0001466512,0.001199506,0.003089827],"genre_scores_gemma":[0.7723185,0.0003276984,0.2258438,0.0001043992,0.00005234386,0.00005623995,0.0001351059,0.000170154,0.0009916831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003541685,"threshold_uncertainty_score":0.0187304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0195318347229022,"score_gpt":0.3277781620030093,"score_spread":0.3082463272801071,"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."}}