{"id":"W2027009400","doi":"10.1118/1.4889311","title":"TU‐F‐BRE‐03: Application of a Novel Mass‐Density Compensation Optimization Method to Improve the Response of a Liquid‐Filled Ionization Chamber in Nonstandard Fields","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiation Detection and Scintillator Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital Notre-Dame","funders":"","keywords":"Detector; Ionization chamber; Monte Carlo method; Physics; Optics; Sobp; Dosimetry; Computational physics; Ionization; Proton therapy; Nuclear medicine; Beam (structure); Mathematics; Ion","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009722657,0.00009691306,0.0002188763,0.00007486089,0.00005458117,0.00001009669,0.0001270534,0.00008777943,0.00003901279],"category_scores_gemma":[0.0002682804,0.00007688529,0.0000601525,0.0005076603,0.00006919035,0.00006361243,0.00003375467,0.0001683852,0.000003606162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003120436,"about_ca_system_score_gemma":0.00006546998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008269517,"about_ca_topic_score_gemma":0.000007471065,"domain_scores_codex":[0.9988457,0.0001489199,0.0003658924,0.0001829328,0.0003497122,0.0001068185],"domain_scores_gemma":[0.9989508,0.0003033953,0.0002339659,0.0002764918,0.0001886072,0.00004678278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001696099,0.0006355054,0.007026698,0.00005731308,0.00009801844,2.424275e-7,0.002248873,0.6202401,0.04097094,0.04451601,0.0003184504,0.2821917],"study_design_scores_gemma":[0.001092677,0.0001977233,0.001908816,0.00003620333,0.0000169846,2.950362e-7,0.0001608157,0.8962112,0.09868304,0.001271821,0.0002866485,0.0001337595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1862646,0.000001269807,0.8119661,0.001131708,0.00006767821,0.0002846148,0.000008978404,0.00002524181,0.0002498315],"genre_scores_gemma":[0.9915829,5.686535e-7,0.008140737,0.00011424,0.00008616683,0.00003814964,0.000009069536,0.000008758328,0.00001936064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8053184,"threshold_uncertainty_score":0.3135291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009397944699805514,"score_gpt":0.2692453161147893,"score_spread":0.2598473714149838,"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."}}