{"id":"W2995324767","doi":"10.3174/ajnr.a6368","title":"Lateral Decubitus Digital Subtraction Myelography: Tips, Tricks, and Pitfalls","year":2019,"lang":"en","type":"review","venue":"American Journal of Neuroradiology","topic":"Neurosurgical Procedures and Complications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital","funders":"","keywords":"Myelography; Medicine; Subtraction; Fluoroscopy; Radiology; Digital subtraction angiography; Image subtraction; Nuclear medicine; Angiography; Spinal cord; Computer science; Artificial intelligence; Image processing; Image (mathematics)","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":[0.00009635615,0.0003156921,0.002352241,0.0004604003,0.00004269334,0.00004104618,0.0001932854,0.0001215984,0.00001431933],"category_scores_gemma":[0.0001219784,0.0002216896,0.0006484891,0.0004568766,0.0003478309,0.0001094444,0.00003418148,0.0009380312,0.00002267049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003512282,"about_ca_system_score_gemma":0.0002405984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000322145,"about_ca_topic_score_gemma":1.277615e-7,"domain_scores_codex":[0.998202,0.0001708919,0.0008559808,0.0003306204,0.0001654467,0.0002750105],"domain_scores_gemma":[0.9975628,0.0004879016,0.001281077,0.000274815,0.0001203194,0.0002731328],"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":[0.00008772538,0.00008967452,0.0005124673,0.0007007873,0.0001997046,0.0002295165,0.000007762593,1.657313e-7,0.000004458639,0.00007250653,0.0007101584,0.9973851],"study_design_scores_gemma":[0.0003438903,0.002827639,0.001295333,0.0006459245,0.0008546084,0.05722508,0.000007529244,0.000001659267,1.005895e-7,0.00004633864,0.936586,0.0001658918],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004353145,0.9937209,0.0001184495,0.0005121908,0.0004135938,0.0003646997,0.00002528727,0.00002159797,0.0004701632],"genre_scores_gemma":[0.01758732,0.9812855,0.00007253169,0.0005162348,0.0003457071,0.000006197149,0.00002135744,0.00004765294,0.0001174767],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9972192,"threshold_uncertainty_score":0.9040239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04377945195585551,"score_gpt":0.3446164658825921,"score_spread":0.3008370139267366,"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."}}