{"id":"W1997457563","doi":"10.1118/1.3244104","title":"Sci—Wed PM: Delivery—12: The Radiofrequency Noise from MLCs for a Linac‐MR System","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Noise (video); Imaging phantom; Linear particle accelerator; Radiofrequency coil; Physics; Electromagnetic coil; Nuclear magnetic resonance; Acoustics; Computer science; Optics; Artificial intelligence; Beam (structure)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006526685,0.000467433,0.0003165676,0.0006718712,0.0009454988,0.002054642,0.0005839532,0.001145626,0.3318553],"category_scores_gemma":[0.0007294324,0.0003606373,0.0003084019,0.000371664,0.0005502981,0.000810097,0.001236926,0.001168395,0.1220714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001303204,"about_ca_system_score_gemma":0.0004954797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008911807,"about_ca_topic_score_gemma":0.001961281,"domain_scores_codex":[0.9997154,0.00003495128,0.00001219089,0.00003817211,0.000156434,0.00004280794],"domain_scores_gemma":[0.9995043,0.00006659733,0.0000280012,0.00009862216,0.000190785,0.000111633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001808793,0.0003955897,0.004358952,0.0008515239,0.00006234943,0.0009540659,0.0003976955,0.00130243,0.1322635,0.00721913,0.631955,0.2184309],"study_design_scores_gemma":[0.00012065,0.0007655328,0.01028504,0.0001540016,0.0000227384,0.0005809327,0.00009550957,0.002285707,0.06287757,0.0009305491,0.9218467,0.0000350025],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06372453,0.003280435,0.01850549,0.005514415,0.006399894,0.00100562,0.005172168,0.01317623,0.8832212],"genre_scores_gemma":[0.0880044,0.001031385,0.003968682,0.0009299287,0.001583352,0.0001937577,0.002674681,0.002184425,0.8994294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3318553,"threshold_uncertainty_score":0.9530273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0224029687779662,"score_gpt":0.3082451166568677,"score_spread":0.2858421478789014,"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."}}