{"id":"W2041964760","doi":"10.1118/1.2948409","title":"Monte Carlo calculation of helical tomotherapy dose delivery","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Tomotherapy; Multileaf collimator; Monte Carlo method; Imaging phantom; Collimated light; Rotation (mathematics); Radiation treatment planning; Dosimetry; Physics; Collimator; Projection (relational algebra); Superposition principle; Linear particle accelerator; Image-guided radiation therapy; Beam (structure); Convolution (computer science); Radiosurgery; Optics; Medical imaging; Nuclear medicine; Computer science; Mathematics; Radiation therapy; Algorithm; Artificial intelligence; Medicine; Statistics","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":[0.0007889242,0.0003687974,0.0007424764,0.0009118284,0.0007454867,0.0008623242,0.00106351,0.00104578,0.004538977],"category_scores_gemma":[0.003806407,0.0005817034,0.0007084038,0.001037458,0.0003773381,0.0004382937,0.000306079,0.0005714066,0.0009715095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002019868,"about_ca_system_score_gemma":0.00143079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01451876,"about_ca_topic_score_gemma":0.008547285,"domain_scores_codex":[0.9995033,0.0001237733,0.00002863324,0.00004580643,0.0002465212,0.00005200547],"domain_scores_gemma":[0.9982577,0.0009964176,0.0001056814,0.0001086883,0.0004791467,0.00005236502],"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":[0.00003358699,0.00001286359,0.000344995,0.00002432313,0.00001482908,0.00003655617,0.0000262372,0.9909536,0.001002755,0.003535541,0.0004374982,0.003577418],"study_design_scores_gemma":[0.000006086849,0.00001053593,0.0001806423,0.000005675125,0.000006782333,0.00002035999,0.000004901408,0.997269,0.0009989246,0.0007767834,0.0007123214,0.000008023737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.152157,0.0006966417,0.773952,0.0004320538,0.0001665041,0.0004905485,0.001206386,0.003398787,0.06750001],"genre_scores_gemma":[0.7966483,0.0003552867,0.1903362,0.0002132901,0.00004792558,0.0005205252,0.0008417507,0.0009388246,0.01009795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01451876,"threshold_uncertainty_score":0.0288685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389857757433463,"score_gpt":0.2796589970443578,"score_spread":0.2657604194700232,"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."}}