{"id":"W2045151596","doi":"10.1118/1.4887959","title":"SU‐E‐I‐11: Cascaded Linear System Model for Columnar CsI Flat Panel Imagers with Depth Dependent Gain and Blur","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Calibration and Measurement Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Monte Carlo method; Optics; Detective quantum efficiency; Scintillator; Physics; Optical transfer function; Photon; Materials science; Flat panel detector; Detector; Image quality; Mathematics; Image (mathematics); Computer science","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":[0.0002661991,0.0005035448,0.0003364811,0.0001636556,0.0002398048,0.0003813875,0.0008996037,0.0007440264,0.001452408],"category_scores_gemma":[0.0004308065,0.0003755116,0.0004799044,0.0002126216,0.0002652128,0.0004686217,0.0002378722,0.0005496589,0.0004169672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001203369,"about_ca_system_score_gemma":0.0008311721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007463465,"about_ca_topic_score_gemma":0.009772421,"domain_scores_codex":[0.9997798,0.00003159626,0.000006123767,0.00003900338,0.0001106305,0.00003296231],"domain_scores_gemma":[0.9997591,0.00008219888,0.00004992108,0.0000279538,0.00006625382,0.00001449535],"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":[0.0001122403,0.00006756707,0.001076477,0.0001279831,0.00003356242,0.0001804974,0.00007677257,0.922815,0.06214647,0.00430325,0.0004978552,0.008562284],"study_design_scores_gemma":[0.00000286672,0.00003143946,0.0001688622,0.000001771136,0.000003647203,0.00001641089,0.000003036928,0.9930248,0.006220166,0.0001543594,0.0003676534,0.000005000702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2453978,0.0007228868,0.7402037,0.0001987528,0.00003746786,0.000188502,0.0005233028,0.001446392,0.01128109],"genre_scores_gemma":[0.9238182,0.0003148132,0.06799244,0.00005537321,0.000008825104,0.0001547476,0.0002048188,0.00008151701,0.007369302],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007463465,"threshold_uncertainty_score":0.01484001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02927619277368813,"score_gpt":0.2319167605930079,"score_spread":0.2026405678193197,"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."}}