{"id":"W3213268982","doi":"10.1088/2057-1976/ac396d","title":"Further investigation of 3D dose verification in proton therapy utilizing acoustic signal, wavelet decomposition and machine learning","year":2021,"lang":"en","type":"article","venue":"Biomedical Physics & Engineering Express","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"PROTO Manufacturing (Canada)","funders":"","keywords":"Imaging phantom; Wavelet; Signal-to-noise ratio (imaging); Proton therapy; Noise (video); SIGNAL (programming language); Monte Carlo method; Computer science; Waveform; Acoustics; Artificial intelligence; Physics; Algorithm; Beam (structure); Mathematics; Optics; Statistics; Telecommunications","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":[0.001233014,0.000490128,0.0004487119,0.0003023853,0.0001214679,0.0005875522,0.0004984245,0.0008514012,0.001020668],"category_scores_gemma":[0.002991906,0.0002410983,0.0005127836,0.0003682553,0.0003330358,0.000911669,0.000498916,0.0005575074,0.0001917148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004383611,"about_ca_system_score_gemma":0.0006214203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001699756,"about_ca_topic_score_gemma":0.001832935,"domain_scores_codex":[0.999606,0.0001162569,0.00002147731,0.00005016052,0.000181913,0.00002424894],"domain_scores_gemma":[0.9990175,0.0005241209,0.0001170574,0.0001536531,0.0001585271,0.00002915271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003466679,0.0001335829,0.004949688,0.0003555932,0.00009092414,0.0002931915,0.0002332479,0.6926196,0.1554683,0.002793817,0.00060918,0.1421062],"study_design_scores_gemma":[0.000005550874,0.0001122922,0.001596624,0.00001067039,0.00001046783,0.00009561821,0.00002977195,0.9514985,0.0454556,0.0005107727,0.0006554712,0.00001858896],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1867241,0.0005419092,0.8099398,0.000388274,0.00004833539,0.00007254494,0.0001411195,0.001036983,0.001106964],"genre_scores_gemma":[0.747979,0.000350644,0.2504399,0.00009237063,0.00001037505,0.00004212371,0.0001574187,0.000128032,0.000800143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001699756,"threshold_uncertainty_score":0.006520867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02016296859815073,"score_gpt":0.2618118085032238,"score_spread":0.241648839905073,"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."}}