{"id":"W2015283016","doi":"10.1097/01.hp.0000342828.21935.e4","title":"Study of the Influence of Radionuclide Biokinetics on the Efficiency of In Vivo Counting Using Monte Carlo Simulation","year":2009,"lang":"en","type":"article","venue":"Health Physics","topic":"Radioactivity and Radon Measurements","field":"Health Professions","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Counting efficiency; Monte Carlo method; In vivo; Radionuclide; Internal dosimetry; Whole body counting; Chemistry; Radiochemistry; Environmental science; Biological system; Nuclear medicine; Computer science; Mathematics; Statistics; Dosimetry; Physics; Nuclear physics; Medicine; Detector","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":[0.00155317,0.0004887743,0.000703125,0.0005273955,0.000275691,0.0006244229,0.0005568335,0.0006260453,0.0007596076],"category_scores_gemma":[0.006918245,0.0003229022,0.0004707495,0.0006182813,0.000362409,0.0004616906,0.000293749,0.000502585,0.0001550436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008435919,"about_ca_system_score_gemma":0.0006261518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003998664,"about_ca_topic_score_gemma":0.001557232,"domain_scores_codex":[0.9993118,0.0003010095,0.00003435868,0.00007848116,0.0002242977,0.00005009342],"domain_scores_gemma":[0.9907116,0.0076326,0.0004783721,0.0004032959,0.0007023257,0.00007186658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003071341,0.00009181803,0.005338944,0.0001765948,0.00007011297,0.0001623519,0.0001157071,0.944514,0.03635468,0.003091711,0.0001791362,0.009597731],"study_design_scores_gemma":[0.00001863328,0.0000828398,0.002010888,0.00001487738,0.00003140932,0.00008815416,0.00001798769,0.9643362,0.0323896,0.000433044,0.0005538957,0.00002260366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6256877,0.001185145,0.3655227,0.000185115,0.00003134789,0.0001125612,0.000250333,0.0006087628,0.006416442],"genre_scores_gemma":[0.9622575,0.0004157128,0.03579218,0.0000351579,0.000006672596,0.00006046697,0.0001171889,0.0002169661,0.00109811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003998664,"threshold_uncertainty_score":0.008213997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1577079113018064,"score_gpt":0.4469381941004268,"score_spread":0.2892302827986205,"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."}}