{"id":"W1964134089","doi":"10.1118/1.3002314","title":"Direct‐conversion flat‐panel imager with avalanche gain: Feasibility investigation for HARP‐AMFPI","year":2008,"lang":"en","type":"review","venue":"Medical Physics","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Detective quantum efficiency; Avalanche photodiode; HARP; Optics; Fluoroscopy; Digital radiography; Flat panel detector; Active matrix; Single-photon avalanche diode; Physics; Dynamic range; Detector; Optoelectronics; X-ray detector; Avalanche diode; Materials science; Voltage; Radiography; Image quality; Computer science; Thin-film transistor; Breakdown voltage; Nuclear physics","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":[0.0004359531,0.0003392015,0.0002903202,0.0001756437,0.0001827109,0.0004911272,0.0007107669,0.0006163533,0.0007064262],"category_scores_gemma":[0.0005467258,0.0002215995,0.0002941814,0.0001484379,0.0002326023,0.0007202897,0.0001957609,0.0003618866,0.0002543341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003649789,"about_ca_system_score_gemma":0.0003233295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006132068,"about_ca_topic_score_gemma":0.0006639102,"domain_scores_codex":[0.9997876,0.00003259179,0.000004589142,0.00004252327,0.0001110955,0.00002156525],"domain_scores_gemma":[0.9997174,0.0001157191,0.00003639218,0.00002912663,0.00008144931,0.0000199698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002042165,0.0000989578,0.002599765,0.0002658197,0.00003718399,0.000812086,0.0001842245,0.00839111,0.9481007,0.002782765,0.0004241786,0.03609899],"study_design_scores_gemma":[0.00005587541,0.003038434,0.009181133,0.00003167335,0.00008463828,0.002631629,0.000127613,0.1826656,0.7935534,0.0006298974,0.007910363,0.00008965146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.6673812,0.001762441,0.3235101,0.0005569382,0.00004005965,0.0002486627,0.000126063,0.0009048712,0.005469586],"genre_scores_gemma":[0.9045403,0.000481245,0.09275091,0.00005272001,0.00001582395,0.00005494078,0.00006851112,0.00003076066,0.002004796],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0007107669,"threshold_uncertainty_score":0.002648056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07801426872048223,"score_gpt":0.3190176138174385,"score_spread":0.2410033450969563,"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."}}