{"id":"W1993083963","doi":"10.1049/ip-cds:20020350","title":"Direct-conversion flat-panel X-ray image detectors","year":2002,"lang":"en","type":"article","venue":"IEE Proceedings - Circuits Devices and Systems","topic":"Advanced Semiconductor Detectors and Materials","field":"Engineering","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; University of Saskatchewan","funders":"National Cancer Institute; Natural Sciences and Engineering Research Council of Canada","keywords":"Flat panel detector; X-ray detector; Detector; Fluoroscopy; Flat panel; X-ray; Digital radiography; Optics; Detective quantum efficiency; Radiography; Sensitivity (control systems); Medical physics; Dark current; Computer science; Physics; Optoelectronics; Computer vision; Electronic engineering; Image (mathematics); Image quality; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001705958,0.0003308906,0.0004550626,0.0001378162,0.0001459672,0.0003191852,0.0001823435,0.0001688566,0.00008915953],"category_scores_gemma":[0.00002462489,0.0003008177,0.00006141219,0.0001949052,0.00004618497,0.0006755313,0.00003320827,0.0001357955,0.00009447168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006835329,"about_ca_system_score_gemma":0.000002792869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003535589,"about_ca_topic_score_gemma":0.000002056849,"domain_scores_codex":[0.9985256,0.000008797377,0.0004060741,0.0003825241,0.0002234143,0.000453552],"domain_scores_gemma":[0.9994379,0.00003649796,0.0001120719,0.0001239763,0.00009748988,0.0001920673],"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":[0.000001942718,0.000007494483,0.0009538557,0.001314902,0.00004985595,0.000006379204,0.0009696118,0.00006548126,0.9942817,0.00004082527,0.001113645,0.001194277],"study_design_scores_gemma":[0.003035401,0.0004585159,0.003945383,0.001850105,0.0003391621,0.0004151155,0.005277019,0.1038275,0.6498121,0.0001098005,0.2267679,0.004161982],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983202,0.004933069,0.0001138667,0.000004641862,0.001707433,0.0003656887,0.00002184224,0.0006346428,0.009016781],"genre_scores_gemma":[0.9985512,0.0004764935,0.0000333076,0.00002198747,0.0004254744,0.00004374198,0.000002501953,0.00007601018,0.000369295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3444697,"threshold_uncertainty_score":0.9999444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02489540107055355,"score_gpt":0.2056267412048466,"score_spread":0.180731340134293,"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."}}