{"id":"W2166216246","doi":"10.1109/tmi.2007.903253","title":"Noise Performance of a Precision Pulsed Electromagnet Power Supply for Magnetic Resonance Imaging","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute","keywords":"Electromagnet; Magnet; Resistive touchscreen; Computer science; Robustness (evolution); Noise (video); Voltage; Acoustics; Electromagnetic coil; Imaging phantom; Physics; Electrical engineering; Optics; Engineering; Artificial intelligence; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001947099,0.0001874696,0.0003054119,0.0001794486,0.0002234776,0.000005929434,0.0001629312,0.00006626075,0.0004267269],"category_scores_gemma":[0.00004162994,0.0001709983,0.00015483,0.0003636153,0.0002690243,0.0001461618,0.000002229342,0.0003864233,0.00001083598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006893151,"about_ca_system_score_gemma":0.0001681396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001253965,"about_ca_topic_score_gemma":0.000001512962,"domain_scores_codex":[0.9982887,0.00001896464,0.0004360537,0.0003622511,0.0005213456,0.000372688],"domain_scores_gemma":[0.9989655,0.0001743935,0.00007478749,0.0003852433,0.0001709011,0.0002291544],"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":[0.0008440104,0.000887547,0.001758947,0.00009395793,0.000006310728,0.00004758729,0.0002464729,0.0001814989,0.06787223,0.00005038506,0.002674381,0.9253367],"study_design_scores_gemma":[0.009791167,0.00265113,0.01749106,0.001873987,0.0002850402,0.002519472,0.0001760028,0.4131975,0.4958033,0.0004880344,0.05476062,0.0009626781],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1050249,0.001190541,0.8894426,0.002519049,0.0001117012,0.0008768748,0.00003305938,0.0001937294,0.0006075894],"genre_scores_gemma":[0.9667257,0.001062157,0.03032252,0.0007950489,0.00004953556,0.0003277437,0.000009293074,0.00004352966,0.0006644878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.924374,"threshold_uncertainty_score":0.6973109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009310854405613486,"score_gpt":0.2812655340939756,"score_spread":0.2719546796883622,"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."}}