{"id":"W2063099556","doi":"10.1118/1.2241650","title":"TU‐FF‐A3‐01: X‐Ray and Optical Monte Carlo Study of Thick, Segmented Scintillators for MV Imaging","year":2006,"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":"University of Alberta","funders":"","keywords":"Optics; Monte Carlo method; Detective quantum efficiency; Photon; Photodiode; Physics; Scintillator; Photon energy; Detector; Materials science; Image quality","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":[0.0004866484,0.0002622398,0.0002718828,0.0002431241,0.0002064516,0.0004462618,0.0004634556,0.0005198318,0.001430056],"category_scores_gemma":[0.001057045,0.0002755441,0.0002790031,0.000355382,0.0002401938,0.0002355568,0.0001580418,0.0002086816,0.000142734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008004854,"about_ca_system_score_gemma":0.0005845755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004727815,"about_ca_topic_score_gemma":0.002678144,"domain_scores_codex":[0.999894,0.00003509793,0.000003354846,0.00001197229,0.00003986322,0.00001572684],"domain_scores_gemma":[0.9993359,0.0004010356,0.00008525034,0.00003941742,0.0001052006,0.00003307247],"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":[0.0007247803,0.0001269815,0.008077297,0.0002036895,0.00008672701,0.0004400673,0.0001485764,0.8840165,0.0885483,0.004756071,0.0006946314,0.01217649],"study_design_scores_gemma":[0.00002553295,0.0001232999,0.00184088,0.000008992419,0.00001407129,0.0001089387,0.00001300579,0.9692912,0.02776829,0.0002137662,0.0005813483,0.00001075335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9378294,0.0004484355,0.05541465,0.00008120586,0.00001250605,0.000048196,0.0002266174,0.0005453097,0.005393704],"genre_scores_gemma":[0.977831,0.00008830857,0.02065168,0.00002095175,0.000002685671,0.00003608092,0.0001106745,0.00009357438,0.00116497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004727815,"threshold_uncertainty_score":0.009400606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008264339350245247,"score_gpt":0.2490995306128514,"score_spread":0.2408351912626061,"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."}}