{"id":"W2541015677","doi":"10.1088/0031-9155/61/22/8044","title":"A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT","year":2016,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Ministère de la Santé et des Services sociaux","keywords":"Monte Carlo method; Energy (signal processing); Computer science; Elemental analysis; Computational physics; Calibration; Materials science; Biological system; Physics; Chemistry; Mathematics; Statistics","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":[0.00006590421,0.0001021055,0.0001901606,0.00003993583,0.00001927744,0.000001596549,0.00003826449,0.00002202857,0.000001151674],"category_scores_gemma":[0.00002089077,0.00005933833,0.0000107072,0.00007866267,0.00004813569,0.00004633002,0.00001097812,0.00003824802,4.177111e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002176387,"about_ca_system_score_gemma":0.000003952653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001438873,"about_ca_topic_score_gemma":0.00008198307,"domain_scores_codex":[0.9995335,0.0000217212,0.0001042156,0.0001491719,0.00002265903,0.0001687704],"domain_scores_gemma":[0.9996909,0.0001518414,0.00001749423,0.00007571293,0.00002012451,0.0000438911],"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":[0.00006056937,0.0000135514,0.0009808777,0.00002600541,0.00004401552,0.000004347272,0.0006107679,0.03550227,0.2343423,0.002579261,0.0001054215,0.7257306],"study_design_scores_gemma":[0.01982531,0.003177892,0.006007734,0.0009158553,0.0002551045,0.00008790506,0.00111631,0.5919651,0.2625553,0.02945038,0.08263198,0.002011067],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1657154,0.0002021912,0.8335644,0.0002949031,0.00006541863,0.0001000485,0.000005302346,0.00002187615,0.0000305107],"genre_scores_gemma":[0.8553769,0.00006660949,0.1439263,0.0003235112,0.0001722444,0.00006785787,0.000006434241,0.00001467016,0.00004546617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7237195,"threshold_uncertainty_score":0.2419747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1098600495110488,"score_gpt":0.3849552635522207,"score_spread":0.2750952140411719,"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."}}