{"id":"W1507960332","doi":"10.1120/jacmp.v12i4.3589","title":"Patient‐specific CT dosimetry calculation: a feasibility study","year":2011,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; National Research Council Canada; National Institutes of Health","keywords":"Imaging phantom; Dosimetry; Computer science; Monte Carlo method; Radiation treatment planning; Nuclear medicine; Scanner; Dosimeter; Medical physics; Algorithm; Radiation therapy; Physics; Mathematics; Medicine; Artificial intelligence; Radiology; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001103763,0.0002122914,0.0006772665,0.00003774096,0.00007383944,0.00001541013,0.0004022421,0.00007015591,0.001017451],"category_scores_gemma":[0.00005312879,0.0001609646,0.0003796609,0.0002570002,0.0002505687,0.0001441944,0.0000840963,0.001100529,0.00001115116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000467523,"about_ca_system_score_gemma":0.0001400643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006515802,"about_ca_topic_score_gemma":1.753596e-7,"domain_scores_codex":[0.996887,0.0001439368,0.001534702,0.0002931372,0.000896823,0.0002443916],"domain_scores_gemma":[0.9977205,0.0004249967,0.000864359,0.0004220722,0.0001501247,0.0004179141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006842226,0.01134217,0.3427677,0.000008016001,0.0004880911,0.00006435366,0.0007817096,0.00001027317,0.00006827444,0.01064687,0.002147579,0.6309907],"study_design_scores_gemma":[0.02789664,0.01454544,0.3041224,0.0003854388,0.0008030764,0.00004941902,0.003433951,0.0006687307,0.0197435,0.6007279,0.02478241,0.002841172],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7577577,0.00005163316,0.2341934,0.00003975694,0.0005473851,0.0005464329,0.000005170293,0.00004626818,0.006812298],"genre_scores_gemma":[0.9879218,0.00001527728,0.01005672,0.0002054467,0.001753757,0.00001021262,0.000001905916,0.00002904283,0.000005859283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6281496,"threshold_uncertainty_score":0.9998958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0610505804364096,"score_gpt":0.3752938721396518,"score_spread":0.3142432917032422,"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."}}