{"id":"W1678065162","doi":"10.1109/nssmic.1996.591410","title":"A more physical approach to model the surface treatment of scintillation counters and its implementation into DETECT","year":2002,"lang":"en","type":"article","venue":"1996 IEEE Nuclear Science Symposium. Conference Record","topic":"Calibration and Measurement Techniques","field":"Engineering","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"TRIUMF","funders":"","keywords":"Scintillation; Parametrization (atmospheric modeling); Monte Carlo method; Photon; Surface roughness; Flexibility (engineering); Optics; Detector; Reflector (photography); Physics; Photon counting; Range (aeronautics); Computer science; Surface (topology); Electronic engineering; Aerospace engineering; Engineering; Radiative transfer; Mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001612938,0.0001411446,0.000148168,0.00009453459,0.0001521928,0.0001159065,0.0001869469,0.00002989374,0.00001384994],"category_scores_gemma":[0.000005180585,0.0001084459,0.00003621974,0.0003393833,0.0001259111,0.0003743448,0.00002047746,0.00004839719,0.00000791022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001515954,"about_ca_system_score_gemma":0.00003076938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008676458,"about_ca_topic_score_gemma":0.00003168924,"domain_scores_codex":[0.9990096,0.00001775954,0.0001788266,0.0002517831,0.0003397111,0.000202334],"domain_scores_gemma":[0.9995466,0.00001340481,0.00004521587,0.0001914884,0.0001056527,0.00009761914],"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":[0.000008155684,0.00004432758,0.0000702406,0.00002207055,0.000009734827,1.109947e-7,0.01076462,0.02477869,0.9354731,0.0006027187,0.0001891489,0.02803712],"study_design_scores_gemma":[0.0001448393,0.0001527256,0.0001305947,0.00001235856,0.00001231454,0.00000162139,0.0004319064,0.9484023,0.05027408,0.00004391377,0.0002756065,0.0001177548],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914938,0.00001078654,0.00599685,0.0002730311,0.00008472563,0.0005093294,0.000006010359,0.0001571085,0.001468355],"genre_scores_gemma":[0.99446,0.0001945233,0.005221722,0.00004283283,0.00002101774,0.00001966404,6.566447e-7,0.00001540136,0.00002419532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9236236,"threshold_uncertainty_score":0.4422297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04214478848547271,"score_gpt":0.2739919241400693,"score_spread":0.2318471356545966,"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."}}