{"id":"W2044602818","doi":"10.1016/j.ijrobp.2005.07.588","title":"Anatomy-based MLC Field Optimization for the Treatment of Gynecologic Malignancies","year":2005,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Hôtel-Dieu de Québec; Centre hospitalier universitaire de Québec","funders":"","keywords":"Medicine; Pelvis; Parametrial; Radiation treatment planning; Rectum; Cervical cancer; Radiology; Radiation therapy; Female pelvis; Nuclear medicine; Surgery; Cancer; Cervical carcinoma","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":[0.000564097,0.0005093942,0.0004032678,0.0008151477,0.0002814858,0.0005827436,0.0004360088,0.0004076192,0.002977572],"category_scores_gemma":[0.002000916,0.0002927322,0.0003810904,0.0004901213,0.000208379,0.0004294076,0.0005838547,0.000573843,0.000576066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007220157,"about_ca_system_score_gemma":0.001038879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002153452,"about_ca_topic_score_gemma":0.00293311,"domain_scores_codex":[0.9997939,0.00006108727,0.000009240387,0.00001727496,0.0001015401,0.00001684596],"domain_scores_gemma":[0.9996517,0.0001600931,0.00003248068,0.00002610324,0.0001098013,0.00001986027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005871694,0.0001027546,0.002627551,0.0002138541,0.00004704005,0.00006924284,0.0001458602,0.7105256,0.04746496,0.002939674,0.005333331,0.229943],"study_design_scores_gemma":[0.00009310497,0.0001503275,0.003640494,0.00002012973,0.00005589226,0.0002444778,0.0000579526,0.9639036,0.02177237,0.003386953,0.006637171,0.00003753922],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08763063,0.002444885,0.8926141,0.001158611,0.0001424582,0.0001940821,0.0003913092,0.003362786,0.01206117],"genre_scores_gemma":[0.7857609,0.0007486304,0.206833,0.0003229189,0.00008344541,0.0001410748,0.0003921605,0.001239625,0.00447813],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002977572,"threshold_uncertainty_score":0.009961009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01546699727596394,"score_gpt":0.3365164737310979,"score_spread":0.3210494764551339,"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."}}