{"id":"W2596359566","doi":"10.1117/12.2256483","title":"Preliminary development of augmented reality systems for spinal surgery","year":2017,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Augmented reality; Computer science; Visualization; Computer vision; Imaging phantom; Overlay; Artificial intelligence; Mixed reality; Navigation system; Human–computer interaction; Radiology; Medicine","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":[0.003933245,0.001035116,0.0004761592,0.001094557,0.0004354308,0.002342005,0.00168866,0.001704095,0.009838199],"category_scores_gemma":[0.004132947,0.0006424166,0.0009452087,0.0007028211,0.0006619431,0.001965763,0.001194446,0.001392529,0.003010867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000627927,"about_ca_system_score_gemma":0.0009777676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001434506,"about_ca_topic_score_gemma":0.001430516,"domain_scores_codex":[0.9977411,0.000579199,0.0001423717,0.0002575598,0.001150714,0.0001290636],"domain_scores_gemma":[0.9959196,0.000782809,0.0001312692,0.0005322358,0.002437672,0.0001964272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007434876,0.0002958128,0.002496678,0.001887727,0.0001640048,0.0007287672,0.001159984,0.01751289,0.1350339,0.04735623,0.01267026,0.7799501],"study_design_scores_gemma":[0.0001419677,0.004573245,0.0104655,0.001450719,0.0002611407,0.002627891,0.0004961623,0.07975076,0.2302028,0.01173488,0.6579321,0.0003627375],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04360519,0.02873447,0.8655784,0.002456993,0.0018073,0.0007562148,0.001182472,0.002316809,0.05356217],"genre_scores_gemma":[0.2590825,0.02076969,0.6817958,0.0007858432,0.0005775125,0.0006585048,0.002293895,0.0003130134,0.03372329],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009838199,"threshold_uncertainty_score":0.03291202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03403699889698883,"score_gpt":0.2737043799265529,"score_spread":0.2396673810295641,"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."}}