{"id":"W1968689318","doi":"10.1016/j.clon.2007.02.002","title":"A Computed Tomography-based Protocol vs Conventional Clinical Mark-up for Breast Electron Boost","year":2007,"lang":"en","type":"article","venue":"Clinical Oncology","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Computed tomography; Nuclear medicine; Radiation treatment planning; Tomography; Radiology; Breast-conserving surgery; Radiation therapy; Margin (machine learning); Breast cancer; Mastectomy; Cancer; Internal medicine","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":[0.002441603,0.0005610307,0.0006349467,0.001117012,0.0004427139,0.0005752816,0.0007177102,0.0007647703,0.006709145],"category_scores_gemma":[0.005670449,0.0002783779,0.0003361369,0.0009297561,0.0004714217,0.0006580182,0.000631402,0.0007669239,0.0008801789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005069183,"about_ca_system_score_gemma":0.0008959438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001393591,"about_ca_topic_score_gemma":0.00202725,"domain_scores_codex":[0.9992902,0.0003475225,0.0001098193,0.00009340684,0.00009392296,0.00006510111],"domain_scores_gemma":[0.9988284,0.0005393309,0.000140773,0.0001926028,0.0002073933,0.00009154493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.08607589,0.00611227,0.09456968,0.001893307,0.0004701326,0.00138832,0.000681192,0.01436403,0.1208835,0.00607038,0.008499919,0.6589914],"study_design_scores_gemma":[0.01244831,0.07099212,0.5326709,0.0009735698,0.003054203,0.01318949,0.001597206,0.05524165,0.2113178,0.007032535,0.09093566,0.0005466437],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.861752,0.007030014,0.07575344,0.002185324,0.0008626062,0.0114433,0.001942003,0.0007839201,0.03824731],"genre_scores_gemma":[0.9030535,0.002447109,0.08105814,0.0005330756,0.0001551984,0.004445224,0.000818803,0.0002817348,0.00720726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006709145,"threshold_uncertainty_score":0.02244437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04968701917228183,"score_gpt":0.4500640112685209,"score_spread":0.4003769920962391,"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."}}