{"id":"W4241449978","doi":"10.1109/nssmic.2001.1008670","title":"Design considerations for efficient binary megavoltage photon detector structures","year":2005,"lang":"en","type":"article","venue":"2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310)","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Detector; Monte Carlo method; Binary number; Photon; Image resolution; Quantum efficiency; Computer science; Electronic engineering; Detective quantum efficiency; Optics; Physics; Engineering; Mathematics; Artificial intelligence; Image quality","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006115765,0.0005328805,0.0004561688,0.0004160103,0.0009960923,0.0004970471,0.0007568279,0.0001719717,0.0006649312],"category_scores_gemma":[0.0002143241,0.0005372433,0.0001462106,0.000609991,0.0005955611,0.0009772321,0.00008655295,0.0003025683,0.000358286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000452972,"about_ca_system_score_gemma":0.0004030135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003158892,"about_ca_topic_score_gemma":0.00003360494,"domain_scores_codex":[0.9965954,0.00006136637,0.0005989506,0.0008603202,0.0005486244,0.00133531],"domain_scores_gemma":[0.9978947,0.0003263931,0.0001510754,0.0006969059,0.0004837454,0.0004471585],"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":[0.00003896893,0.00004851469,0.00001067414,0.0000400907,0.000015531,0.000005780856,0.0005686803,0.1343798,0.8590235,0.0004560731,0.0006965115,0.004715917],"study_design_scores_gemma":[0.0005177659,0.00019704,0.00005817362,0.00006062282,0.00003236265,0.00003596423,0.0001774831,0.9407049,0.05599442,0.000660638,0.0009011396,0.0006594367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9171219,0.000001703174,0.07737627,0.0002136475,0.001964908,0.0009936203,0.00004188199,0.0007394701,0.001546587],"genre_scores_gemma":[0.3091953,0.0001598699,0.6897042,0.0002581827,0.0003076808,0.00008295527,0.000002890985,0.00008922628,0.0001996821],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8063252,"threshold_uncertainty_score":0.9997079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02649554845167776,"score_gpt":0.2491975327571898,"score_spread":0.222701984305512,"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."}}