{"id":"W2044413413","doi":"10.1016/j.nima.2011.07.036","title":"Feasibility of fast neutron analysis for the detection of explosives buried in soil","year":2011,"lang":"en","type":"article","venue":"Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Nuclear Laboratories; Defence Research and Development Canada","funders":"","keywords":"Explosive material; Explosive detection; Neutron generator; Neutron activation analysis; Neutron; Nuclear engineering; Computer science; Neutron source; Engineering; Physics; 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":[0.0009137083,0.000608295,0.0003102134,0.0006375399,0.0004379571,0.0007026537,0.0005446349,0.0009931674,0.001534609],"category_scores_gemma":[0.001323722,0.0003739075,0.0002834733,0.0003029757,0.0004636317,0.0006850231,0.0003446162,0.0004170865,0.0003559186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003397141,"about_ca_system_score_gemma":0.000700132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001161022,"about_ca_topic_score_gemma":0.002379169,"domain_scores_codex":[0.9996397,0.00009650458,0.00001152308,0.00009604386,0.0001211754,0.00003496181],"domain_scores_gemma":[0.9990349,0.0005674027,0.00006794916,0.00004913134,0.0002341928,0.00004646519],"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":[0.001824933,0.00006925836,0.0125483,0.0001428061,0.00003871494,0.0001838889,0.00005263033,0.000803754,0.9658254,0.0004065248,0.0001297332,0.01797416],"study_design_scores_gemma":[0.0002371333,0.002663443,0.05096549,0.00008180692,0.000268185,0.002168779,0.0003833829,0.03488689,0.9010373,0.001554557,0.005688585,0.00006442346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.948035,0.001803366,0.04591008,0.000229966,0.00009270191,0.00007247577,0.0003703005,0.0001460839,0.003340058],"genre_scores_gemma":[0.9702238,0.0009302185,0.02707981,0.00006347245,0.00001653594,0.0000243019,0.0002312344,0.00002946203,0.001401084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001534609,"threshold_uncertainty_score":0.005133808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1077287427561184,"score_gpt":0.3912367393115214,"score_spread":0.283507996555403,"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."}}