{"id":"W3094476452","doi":"10.1016/j.ijrobp.2020.07.1534","title":"Is the Promise of Diffusion-weighed (DWI) MRI based Therapy Response Prediction in Advanced Cervical Cancer Ready for Prime Time in Standard Community Settings? The Issue of Standardized Postprocessing","year":2020,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Endometrial and Cervical Cancer Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Contouring; Effective diffusion coefficient; Diffusion MRI; Nuclear medicine; Radiology; Magnetic resonance imaging; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03754354,0.000769844,0.001437762,0.00130547,0.0006718235,0.005426058,0.002093209,0.00210262,0.003245493],"category_scores_gemma":[0.09510113,0.0006146802,0.0008749044,0.001656998,0.001850156,0.005859186,0.001503496,0.004383635,0.001356909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0013135,"about_ca_system_score_gemma":0.004646287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005222033,"about_ca_topic_score_gemma":0.01023644,"domain_scores_codex":[0.9935429,0.003500834,0.0009482381,0.0006079901,0.001079916,0.0003201007],"domain_scores_gemma":[0.9300849,0.03037417,0.007630448,0.009991885,0.0199416,0.001976995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00253789,0.0005780527,0.08700374,0.001645069,0.0004534793,0.0003010838,0.001311794,0.003977986,0.01042769,0.01151396,0.07345366,0.8067954],"study_design_scores_gemma":[0.001664101,0.007794346,0.4072333,0.006247486,0.001801791,0.004125647,0.008309199,0.07106943,0.04466081,0.1156514,0.3303253,0.001117161],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2910702,0.06036225,0.2515709,0.3518956,0.01433666,0.001279893,0.004561136,0.003590622,0.02133282],"genre_scores_gemma":[0.6149273,0.02612485,0.3069891,0.03176577,0.01177033,0.0008920662,0.002758617,0.001158145,0.003613857],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03754354,"threshold_uncertainty_score":0.1985515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03470141596575154,"score_gpt":0.3743980045843808,"score_spread":0.3396965886186292,"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."}}