{"id":"W4319350142","doi":"10.1186/s13014-023-02209-4","title":"Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience","year":2023,"lang":"en","type":"article","venue":"Radiation Oncology","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Radiation treatment planning; Magnetic resonance imaging; Radiation therapy; Medical physics; Quality assurance; Radiology; Workflow; External beam radiotherapy; Surgical planning; Nuclear medicine; Brachytherapy; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004511154,0.0001055805,0.0002544455,0.000154038,0.00008509959,0.000008511784,0.0001096282,0.00007926962,0.0002583785],"category_scores_gemma":[0.00004520749,0.000119474,0.00008529742,0.0002593719,0.00007271917,0.0001961861,0.00001857295,0.00009231023,0.000006377777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001787754,"about_ca_system_score_gemma":0.0001701516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003125558,"about_ca_topic_score_gemma":0.000001768266,"domain_scores_codex":[0.9986727,0.0001499996,0.0005847527,0.0002652579,0.0001031263,0.0002241626],"domain_scores_gemma":[0.9985045,0.0007732594,0.0004275072,0.0001546497,0.00009381546,0.00004626091],"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":[0.00008917267,0.00004723173,0.2760575,0.000004543248,0.000008403583,5.938194e-7,0.001540175,0.003080938,0.0007343654,0.00246801,0.001487931,0.7144812],"study_design_scores_gemma":[0.005238638,0.001004541,0.252215,0.00001113193,0.00002901859,7.066237e-7,0.00206838,0.1027385,0.002471924,0.002645424,0.6313341,0.000242636],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.467668,0.0008697462,0.5254596,0.0008122366,0.001064749,0.002140186,0.0001612148,0.0003268776,0.001497318],"genre_scores_gemma":[0.9839573,0.0000803306,0.01457419,0.0001247808,0.0005316581,0.0003439544,0.0002784496,0.00002588536,0.0000834891],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7142385,"threshold_uncertainty_score":0.4872006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0370056649676687,"score_gpt":0.4801156923553101,"score_spread":0.4431100273876414,"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."}}