{"id":"W2141535361","doi":"10.1109/jproc.2002.1002529","title":"Direct-conversion flat-panel X-ray image sensors for digital radiography","year":2002,"lang":"en","type":"article","venue":"Proceedings of the IEEE","topic":"Advanced Semiconductor Detectors and Materials","field":"Engineering","cited_by":217,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Saskatchewan","funders":"","keywords":"Detective quantum efficiency; Flat panel detector; Flat panel; X-ray detector; Detector; Digital radiography; Quantum efficiency; Optics; X-ray; Radiography; Image quality; Active matrix; Sensitivity (control systems); Optoelectronics; Noise (video); Physics; Computer science; Image (mathematics); Electronic engineering; Computer vision; Engineering","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":[0.0003339082,0.0003332454,0.0003243338,0.0003931734,0.0003029413,0.000871037,0.0006592825,0.0006486829,0.0081582],"category_scores_gemma":[0.0008312312,0.0002901509,0.0002052763,0.0005149625,0.0004439731,0.0008826937,0.0003302846,0.0008248755,0.00272013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004134396,"about_ca_system_score_gemma":0.0005159808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002355995,"about_ca_topic_score_gemma":0.0009479942,"domain_scores_codex":[0.9996012,0.00005550665,0.00001333862,0.00004052628,0.0002717322,0.00001775016],"domain_scores_gemma":[0.9997126,0.0001186061,0.00002341777,0.00003394254,0.00009555375,0.00001581078],"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":[0.0001368445,0.0001087322,0.0008074733,0.0009861224,0.00001975749,0.0003250327,0.000134842,0.002123224,0.5859929,0.09385196,0.01129524,0.3042178],"study_design_scores_gemma":[0.00004977618,0.0006096754,0.004253936,0.0003042549,0.00006496187,0.003426406,0.0001562187,0.03484289,0.5858405,0.02992262,0.3404247,0.0001040411],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03775239,0.03078935,0.8568392,0.001426818,0.0007712515,0.0004243314,0.0003826075,0.002694462,0.06891945],"genre_scores_gemma":[0.2619098,0.01864156,0.6635332,0.0007138689,0.0003252129,0.0002451065,0.0004315817,0.0001710193,0.05402862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0081582,"threshold_uncertainty_score":0.02729189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01457911906300772,"score_gpt":0.1914744981918888,"score_spread":0.1768953791288811,"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."}}