{"id":"W4405293066","doi":"10.1016/j.brachy.2024.11.007","title":"Towards U-Net-based intraoperative 2D dose prediction in high dose rate prostate brachytherapy","year":2024,"lang":"en","type":"article","venue":"Brachytherapy","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Ontario Institute for Cancer Research; Ministerio de Economía y Competitividad; Prostate Cancer Canada; London Health Sciences Foundation","keywords":"Medicine; Brachytherapy; Prostate brachytherapy; Dose rate; Prostate; Radiology; Medical physics; Nuclear medicine; Oncology; Internal medicine; Radiation therapy; Cancer","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004369363,0.0007608377,0.0006073855,0.0006576706,0.0002397207,0.001326219,0.001023396,0.000890061,0.001649566],"category_scores_gemma":[0.001411738,0.0005622411,0.0006350462,0.0005231784,0.0002527117,0.0007161676,0.001045249,0.0005953299,0.0008228261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005045896,"about_ca_system_score_gemma":0.0006615814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004950909,"about_ca_topic_score_gemma":0.005944923,"domain_scores_codex":[0.9998136,0.00004338407,0.00001197905,0.00003506319,0.00007665338,0.00001926264],"domain_scores_gemma":[0.9996669,0.0001512644,0.00003983239,0.00003369491,0.00008604362,0.00002228053],"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":[0.000274044,0.00008142844,0.002640715,0.0001355441,0.00007170079,0.000131034,0.00005133302,0.813185,0.01003418,0.002431609,0.002684574,0.1682786],"study_design_scores_gemma":[0.000001630964,0.000008912147,0.0001504654,0.000005550421,0.000004326091,0.00001591693,0.000003765921,0.9977188,0.001284177,0.0004817834,0.000320533,0.000004228905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03510638,0.0008452533,0.9586132,0.0002028405,0.00008346687,0.00005408766,0.0003543643,0.002248448,0.002491947],"genre_scores_gemma":[0.6384203,0.0009007251,0.3553334,0.0002530084,0.00008137191,0.0001168425,0.000733532,0.0004772306,0.003683606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004950909,"threshold_uncertainty_score":0.009844184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501761772697684,"score_gpt":0.2894139743997094,"score_spread":0.2743963566727325,"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."}}