{"id":"W2565674961","doi":"10.1016/j.radmeas.2016.12.008","title":"The spatial dose rate and energy characterization of a P 385 D-D Neutron Generator using a nested neutron spectrometer and a tissue equivalent proportional counter","year":2016,"lang":"en","type":"article","venue":"Radiation Measurements","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada; University Network of Excellence in Nuclear Engineering","keywords":"Neutron generator; Neutron; Spectrometer; Nuclear physics; Equivalent dose; Characterization (materials science); Physics; Proportional counter; Radiochemistry; Neutron temperature; Chemistry; Optics; Detector","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004264357,0.0001334771,0.0001798341,0.0001161923,0.0001275452,0.00003615821,0.00003580248,0.00006440956,0.00006283485],"category_scores_gemma":[0.00004892744,0.00008384883,0.00002988617,0.0001163957,0.00006470956,0.000197448,0.00001289252,0.00004043517,0.0000020819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001279749,"about_ca_system_score_gemma":0.00009920048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002821363,"about_ca_topic_score_gemma":0.000008219571,"domain_scores_codex":[0.9987603,0.0001404919,0.0003543829,0.0002156018,0.0003607519,0.00016848],"domain_scores_gemma":[0.9992764,0.00003637165,0.0002861259,0.0001489661,0.0001568995,0.00009522456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000364882,0.00004676131,0.03566841,0.00001996852,0.00007507735,8.947883e-7,0.00007675461,0.000001853541,0.9384587,0.0000925347,0.00001774294,0.02517637],"study_design_scores_gemma":[0.003200139,0.0003241412,0.8357328,0.00006811669,0.00009576505,0.00001393081,0.000006759481,0.001551271,0.15582,0.00002655495,0.003036673,0.0001238568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956403,0.0002932703,0.002724917,0.0007996639,0.0002045715,0.0002876541,0.00001456851,0.00001701466,0.0000180477],"genre_scores_gemma":[0.9986778,0.0003512829,0.00008210995,0.0002691666,0.0002822147,0.00002259439,0.00003375753,0.00001815395,0.0002628745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8000643,"threshold_uncertainty_score":0.3419256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0330001562360376,"score_gpt":0.2759024956718636,"score_spread":0.242902339435826,"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."}}