{"id":"W3111308105","doi":"10.1002/acm2.13118","title":"Clinical experience of MRI<sup>4D</sup> QUASAR motion phantom for latency measurements in 0.35T MR‐LINAC","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"March of Dimes Canada","funders":"","keywords":"Imaging phantom; Linear particle accelerator; Gating; Physics; Latency (audio); Image-guided radiation therapy; Magnetic resonance imaging; Nuclear medicine; Optics; Computer science; Beam (structure); Medical imaging; Nuclear magnetic resonance; Artificial intelligence; Medicine; Radiology","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":[0.004747004,0.0006965957,0.0004223285,0.000512611,0.0002683377,0.0005824022,0.0006438807,0.0004927419,0.001638922],"category_scores_gemma":[0.007657855,0.0004494911,0.0003316028,0.000384478,0.000553739,0.0005449262,0.0007841277,0.0004884383,0.0007169744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004990713,"about_ca_system_score_gemma":0.0003554874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006372238,"about_ca_topic_score_gemma":0.0007827171,"domain_scores_codex":[0.9975978,0.001341861,0.0001939392,0.0003505654,0.0003653671,0.0001505355],"domain_scores_gemma":[0.9949338,0.00240952,0.0006965231,0.0006549266,0.0009671248,0.0003380728],"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":[0.005820787,0.001126001,0.04637219,0.0004368562,0.0002044703,0.001660011,0.004178471,0.01448309,0.7938902,0.0004964123,0.002001654,0.1293298],"study_design_scores_gemma":[0.0006505486,0.05072735,0.1662941,0.00009477272,0.0005835592,0.01527752,0.00149514,0.03122585,0.7069466,0.0004914032,0.02578323,0.0004299704],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9546283,0.001045634,0.04159995,0.0002833589,0.00004939263,0.0001248293,0.0001792624,0.000551223,0.001537984],"genre_scores_gemma":[0.977484,0.0003126075,0.02054003,0.0001535354,0.00003320878,0.00006672309,0.0002808949,0.0002821479,0.000846847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004747004,"threshold_uncertainty_score":0.02510488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08802666839148958,"score_gpt":0.4123379426303824,"score_spread":0.3243112742388928,"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."}}