{"id":"W1965089234","doi":"10.1118/1.4740198","title":"Sci—Fri PM: Delivery — 03: Spine SBRT: Treating multiple vertebrae using cone‐beam CT image‐guidance and the hexapod robotic couch","year":2012,"lang":"en","type":"article","venue":"Medical Physics","topic":"Management of metastatic bone disease","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto; BC Cancer Agency","funders":"","keywords":"Medicine; Hexapod; Nuclear medicine; Cone beam computed tomography; Cone beam ct; Lumbar vertebrae; Lumbar; Spinal cord; Radiology; Computed tomography; Computer science; Artificial intelligence; Robot","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":[0.0003920165,0.0003879631,0.0002547763,0.0005868577,0.0006449777,0.001010533,0.0005157408,0.0008640626,0.1762356],"category_scores_gemma":[0.0007096183,0.0002309601,0.000407874,0.0002303593,0.0005616508,0.000409816,0.0006938924,0.0006820331,0.05164845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001348899,"about_ca_system_score_gemma":0.0006499242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005648351,"about_ca_topic_score_gemma":0.01297218,"domain_scores_codex":[0.9998516,0.00002252382,0.000009866965,0.00002791821,0.00005648929,0.00003160167],"domain_scores_gemma":[0.9997374,0.00003753862,0.00002967905,0.00004296873,0.00005671656,0.000095641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001936561,0.0007753507,0.008224905,0.0005755195,0.00009194131,0.001130376,0.0001868668,0.001955669,0.05757457,0.00347043,0.6029614,0.3211164],"study_design_scores_gemma":[0.0002439379,0.002277233,0.05205461,0.0002083903,0.00005366777,0.002579171,0.0000823927,0.004109318,0.03465478,0.0009087081,0.9027952,0.00003256807],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1005744,0.004028473,0.02282794,0.0119372,0.003576764,0.002254734,0.007544418,0.008521631,0.8387345],"genre_scores_gemma":[0.2462948,0.002879694,0.009965557,0.003040799,0.002566241,0.0003713905,0.004107048,0.002034281,0.7287403],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1762356,"threshold_uncertainty_score":0.5895667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02656546566980938,"score_gpt":0.2891970998602283,"score_spread":0.2626316341904189,"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."}}