{"id":"W2525942840","doi":"10.1016/j.ijrobp.2016.09.029","title":"Volume of Lytic Vertebral Body Metastatic Disease Quantified Using Computed Tomography–Based Image Segmentation Predicts Fracture Risk After Spine Stereotactic Body Radiation Therapy","year":2016,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Management of metastatic bone disease","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Health Sciences Centre; University of Toronto; Centre hospitalier de l'Université Laval; Sunnybrook Health Science Centre","funders":"Elekta; Medtronic","keywords":"Vertebral body; Medicine; Radiology; Computed tomography; Volume (thermodynamics); Nuclear medicine; Surgery","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008024813,0.0003428503,0.0007067783,0.0005558199,0.00006866693,0.00004402269,0.0003188589,0.0001074182,0.0003492651],"category_scores_gemma":[0.0006189489,0.0002591021,0.0004639376,0.0003055747,0.0002544418,0.0007127905,0.00004368457,0.0003047459,0.00001762859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005301202,"about_ca_system_score_gemma":0.0006963601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002088296,"about_ca_topic_score_gemma":9.44727e-7,"domain_scores_codex":[0.9966414,0.0006787617,0.001286227,0.0003650605,0.0007277517,0.0003008023],"domain_scores_gemma":[0.9953701,0.0003952846,0.00255205,0.000317074,0.001057764,0.0003077424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00702428,0.002897125,0.906636,0.0001426264,0.003746995,0.0002808264,0.0002963314,0.0007576245,0.03129112,0.0004353279,0.0009349591,0.04555676],"study_design_scores_gemma":[0.03103084,0.002257239,0.8716433,0.0003663884,0.0022968,0.00005289697,0.00005656331,0.08074962,0.006293354,0.003120795,0.00171453,0.0004176996],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7884866,0.0005908726,0.2064093,0.002187073,0.001182973,0.000733081,0.0003485635,0.00004325889,0.0000183021],"genre_scores_gemma":[0.9871418,0.000301659,0.01014383,0.001312453,0.0006671706,0.00002540128,0.0003306059,0.00004974428,0.00002731084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1986552,"threshold_uncertainty_score":0.9999861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941698642265895,"score_gpt":0.3269312268990991,"score_spread":0.3075142404764402,"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."}}