{"id":"W2016842419","doi":"10.1118/1.2961932","title":"SU‐GG‐T‐180: Measurement Instrumentation to Determine RF Noise Generated by a Medical Linac","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Linear particle accelerator; Physics; Radio frequency; Optics; Field (mathematics); Dipole; Acoustics; Instrumentation (computer programming); Noise (video); Computational physics; Nuclear magnetic resonance; Computer science; Beam (structure); Telecommunications; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.001122138,0.0005986885,0.0003159531,0.0009006539,0.0003439811,0.0004978699,0.0009227885,0.0006472696,0.003122346],"category_scores_gemma":[0.002844688,0.0002853892,0.0001708264,0.0005810974,0.0004535851,0.0005414766,0.0004840686,0.0004763703,0.001356557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003875471,"about_ca_system_score_gemma":0.0005646233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000268035,"about_ca_topic_score_gemma":0.0003865027,"domain_scores_codex":[0.9988735,0.0002230328,0.00008778299,0.0002065598,0.0005525635,0.00005659022],"domain_scores_gemma":[0.9980646,0.0006523397,0.0002844232,0.0002826133,0.0006052097,0.0001106923],"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":[0.0003547673,0.0001417071,0.01623698,0.0002863894,0.00003309386,0.00013143,0.0003617825,0.00146182,0.9075346,0.001357512,0.002711151,0.0693888],"study_design_scores_gemma":[0.00007100796,0.001422821,0.03214043,0.000039899,0.00009164574,0.001406653,0.0001715983,0.03436952,0.9134211,0.0004784673,0.01631922,0.00006763632],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3209999,0.000654644,0.6607524,0.0004321568,0.0002583358,0.0004066374,0.0008859293,0.009256667,0.006353477],"genre_scores_gemma":[0.8003953,0.000229947,0.1947557,0.000396724,0.00006397868,0.0004141339,0.0006273121,0.0004512382,0.002665669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003122346,"threshold_uncertainty_score":0.01044536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02347540424618915,"score_gpt":0.2273418897601918,"score_spread":0.2038664855140026,"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."}}