{"id":"W3025592469","doi":"10.1016/j.ijrobp.2020.04.045","title":"RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning","year":2020,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre; Jewish General Hospital; Mila - Quebec Artificial Intelligence Institute; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Canada Foundation for Innovation; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Brachytherapy; Radiation; Radiation dose; Medical physics; Radiochemistry; Nuclear medicine; Nuclear engineering; Medicine; Radiation therapy; Physics; Chemistry; Radiology; Nuclear physics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004210183,0.0002580401,0.0004861905,0.0002070372,0.0001029818,0.00004484942,0.0004792445,0.0001763461,0.0003954141],"category_scores_gemma":[0.00009734563,0.000260744,0.0002662049,0.0003504824,0.0001147807,0.0007090588,0.00004279846,0.0008262033,0.00001601682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004182303,"about_ca_system_score_gemma":0.0002112952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003154647,"about_ca_topic_score_gemma":0.000001965011,"domain_scores_codex":[0.9978349,0.0004098076,0.0009337325,0.0002939351,0.0002507272,0.0002769601],"domain_scores_gemma":[0.9976653,0.0003749529,0.001317543,0.0001248936,0.0003694588,0.0001477827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001797057,0.0002195161,0.2997236,0.000002295995,0.0002998389,0.000008595106,0.001226852,0.01670171,0.007956392,0.01102904,0.0001462736,0.6625062],"study_design_scores_gemma":[0.02512992,0.004160056,0.09716886,0.0001011098,0.0001980846,0.0000879357,0.0005536677,0.3447363,0.02002089,0.08632743,0.4197369,0.001778835],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1084242,0.0009920736,0.8847175,0.003796846,0.0009133849,0.0003220359,0.00002720393,0.00009981351,0.0007069622],"genre_scores_gemma":[0.9801242,0.000585846,0.01433896,0.001044661,0.003662423,0.00002381518,0.0001533459,0.00005145456,0.00001530331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8716999,"threshold_uncertainty_score":0.9999845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01574208353411823,"score_gpt":0.3265058821215922,"score_spread":0.310763798587474,"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."}}