{"id":"W4403287662","doi":"10.1016/j.jclepro.2024.143910","title":"Simplified efficiency calibration methods for scintillation detectors used in nuclear remediation","year":2024,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Radiation Detection and Scintillator Technologies","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nuclear Laboratories","funders":"","keywords":"Calibration; Environmental remediation; Environmental science; Scintillation; Detector; Nuclear engineering; Liquid scintillation counting; Process engineering; Waste management; Nuclear physics; Radiochemistry; Physics; Engineering; Chemistry; Contamination; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001037899,0.00009400467,0.0001597371,0.0005383966,0.00007619856,0.0001057307,0.00007586149,0.00006423223,0.00004328263],"category_scores_gemma":[0.0001716948,0.0000811397,0.0001150823,0.000459052,0.00002783899,0.0005770698,0.000007901113,0.0001979048,0.000003264701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009689119,"about_ca_system_score_gemma":0.00005255284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006415059,"about_ca_topic_score_gemma":0.000002425829,"domain_scores_codex":[0.9989644,0.00008618306,0.0004981085,0.0001808714,0.0001517908,0.0001186322],"domain_scores_gemma":[0.9993731,0.0000885443,0.0002610956,0.0001103809,0.0001365658,0.00003027225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001426361,0.00009094746,0.006101592,0.00009033496,0.00007506563,7.810549e-7,0.001574825,0.1367323,0.08825146,0.003036169,0.001796672,0.7621072],"study_design_scores_gemma":[0.001173758,0.0005304552,0.00913218,0.0001962447,0.0001061914,0.00002998236,0.002686176,0.6960904,0.2118926,0.01514232,0.062567,0.0004526977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8939956,0.0000869141,0.1021113,0.001141887,0.002234325,0.0002725829,0.000001437482,0.00007953263,0.00007643599],"genre_scores_gemma":[0.9940484,0.000008252111,0.005006868,0.000008500112,0.0008121095,0.00000557663,0.000001491237,0.00001795463,0.00009084099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7616545,"threshold_uncertainty_score":0.3308781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02149155012208674,"score_gpt":0.3354690186918655,"score_spread":0.3139774685697787,"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."}}