{"id":"W3033040683","doi":"10.2172/1576188","title":"High Energy Micron Scale Pixel Hybrid Detector","year":2019,"lang":"en","type":"report","venue":"","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pixel; Scale (ratio); Detector; Energy (signal processing); Computer science; Physics; Optics","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":[0.0002978983,0.0001808519,0.0003153314,0.0002157864,0.0001376839,0.0006329839,0.0008056912,0.0004686451,0.002823409],"category_scores_gemma":[0.0002210685,0.0001772122,0.0001671491,0.0002400681,0.0001356902,0.0006040335,0.0005393192,0.0003262952,0.0009655373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004422103,"about_ca_system_score_gemma":0.00024997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003140599,"about_ca_topic_score_gemma":0.0008077887,"domain_scores_codex":[0.9996567,0.00001963079,0.000009749431,0.0000846784,0.0002016129,0.00002764675],"domain_scores_gemma":[0.9997806,0.00003638213,0.00002571957,0.00003155931,0.0001081923,0.00001751512],"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":[0.0001051005,0.00005367382,0.00154805,0.00009941322,0.00002559669,0.00009611525,0.00004055858,0.0008437992,0.9635316,0.002626143,0.001477969,0.02955204],"study_design_scores_gemma":[0.00002310182,0.0005291628,0.005532668,0.000009144404,0.00002964822,0.0008186562,0.00004716341,0.0141856,0.9605586,0.0003647894,0.01787786,0.0000236498],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7039037,0.0035728,0.2461084,0.0004751831,0.0003422051,0.0003654049,0.001404329,0.004002422,0.03982563],"genre_scores_gemma":[0.6640942,0.0008044153,0.2978527,0.0003623243,0.00004753073,0.000162231,0.0008889845,0.0001174865,0.0356702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002823409,"threshold_uncertainty_score":0.00944525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006881573785457002,"score_gpt":0.2065178436400735,"score_spread":0.1996362698546165,"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."}}