{"id":"W2502177647","doi":"10.1016/j.brachy.2016.06.009","title":"Failure modes and effects analysis in image-guided high-dose-rate brachytherapy: Quality control optimization to reduce errors in treatment volume","year":2016,"lang":"en","type":"article","venue":"Brachytherapy","topic":"Management of metastatic bone disease","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"McGill University","keywords":"Medicine; Guideline; Quality assurance; Clinical Practice; Brachytherapy; Medical physics; Failure mode and effects analysis; Volume (thermodynamics); Image quality; Radiation treatment planning; Modality (human–computer interaction); Radiology; Reliability engineering; Radiation therapy; Artificial intelligence; Image (mathematics); Computer science; Pathology; Physical therapy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00177235,0.0008024777,0.0006285659,0.001481713,0.000362228,0.0007892738,0.0008105051,0.00047776,0.001304609],"category_scores_gemma":[0.005436369,0.0005165553,0.001056604,0.0006398216,0.0005182588,0.0005079688,0.0004630593,0.0004687019,0.0001639277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001079889,"about_ca_system_score_gemma":0.0007331284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006903884,"about_ca_topic_score_gemma":0.00698867,"domain_scores_codex":[0.9991522,0.0002746577,0.00004544275,0.0001150139,0.0003505031,0.00006211228],"domain_scores_gemma":[0.9962144,0.00209785,0.0006659057,0.0003165376,0.0006213954,0.00008396665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001821917,0.0002587934,0.04844009,0.0004135862,0.000380842,0.000276449,0.0006071843,0.7083513,0.1040644,0.001926021,0.001074196,0.1323853],"study_design_scores_gemma":[0.00006200713,0.0003742159,0.05749434,0.00002126294,0.0002829211,0.0003692614,0.00007859139,0.8957891,0.04378367,0.001052573,0.0006098211,0.00008223012],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5192282,0.001135537,0.4755096,0.0002047532,0.00002419824,0.0001474324,0.0002898481,0.001858106,0.001602317],"genre_scores_gemma":[0.9533532,0.0001042991,0.04492786,0.00002713296,0.000008188292,0.00003845475,0.0001425135,0.0005481691,0.0008501515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006903884,"threshold_uncertainty_score":0.01372743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808168754776027,"score_gpt":0.3186478371087854,"score_spread":0.3005661495610251,"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."}}