{"id":"W2804105000","doi":"10.1088/1361-6560/aac5b9","title":"On the direct acquisition of beam’s-eye-view images in MRI for integration with external beam radiotherapy","year":2018,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Imaging phantom; Optics; Computer science; Beam (structure); Scanner; Projection (relational algebra); Physics; Computer vision; Reduction (mathematics); Artificial intelligence; Mathematics; Algorithm; Geometry","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":[0.0006001476,0.000349075,0.0002690468,0.0003372777,0.000154177,0.000678408,0.000704915,0.0005170393,0.001443592],"category_scores_gemma":[0.001148927,0.0003539201,0.0003176802,0.0002777477,0.0008991748,0.0007633952,0.000569985,0.000394529,0.0008411839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003111286,"about_ca_system_score_gemma":0.0003956357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005677509,"about_ca_topic_score_gemma":0.0006749543,"domain_scores_codex":[0.9996277,0.0001017033,0.00001460332,0.00004939335,0.0001850648,0.00002146743],"domain_scores_gemma":[0.999708,0.0001251479,0.00005340049,0.00004642622,0.0000526906,0.00001434482],"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":[0.0002087028,0.00007086642,0.0009779447,0.0003741202,0.00002377251,0.0007988022,0.0004205203,0.02688464,0.7294959,0.08369192,0.0009579586,0.1560948],"study_design_scores_gemma":[0.00003089183,0.0006859877,0.0031345,0.0001918722,0.00005470668,0.003905952,0.0001297763,0.4326894,0.5235595,0.01328428,0.0222341,0.00009903512],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02157407,0.000697609,0.9721735,0.0001990325,0.00003778633,0.00006244086,0.00001518351,0.0003711527,0.004869276],"genre_scores_gemma":[0.3552422,0.002040685,0.6383535,0.0001189699,0.00004578023,0.00009401522,0.00006743532,0.000147595,0.00388987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001443592,"threshold_uncertainty_score":0.004829288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04363318218118512,"score_gpt":0.375185009431,"score_spread":0.3315518272498149,"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."}}