{"id":"W4234233588","doi":"10.32920/ryerson.14643753","title":"Augmented Reality and Human Factors Applications for the Neurosurgical Operating Room","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Augmented reality; Workflow; Computer science; Human–computer interaction; Overlay; Virtual reality; Key (lock); Object (grammar); Artificial intelligence","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":[0.001195088,0.0006553955,0.0002195555,0.0004444295,0.0004750852,0.002890008,0.0005003709,0.001023429,0.01546125],"category_scores_gemma":[0.002771606,0.0002536962,0.0004720085,0.0004600034,0.0006638501,0.001160442,0.001276762,0.0007202455,0.002050764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004224996,"about_ca_system_score_gemma":0.0005495046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001437318,"about_ca_topic_score_gemma":0.001928101,"domain_scores_codex":[0.9990546,0.0003903378,0.00003806991,0.00008780677,0.0003734737,0.00005567861],"domain_scores_gemma":[0.998836,0.0006443445,0.00006440726,0.0001400908,0.0002479751,0.00006719386],"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":[0.0004620069,0.0002016689,0.00295584,0.001339248,0.0001121908,0.0007368501,0.004874459,0.01751358,0.05935882,0.0651373,0.03416085,0.8131471],"study_design_scores_gemma":[0.000145204,0.00222483,0.0205702,0.001729957,0.0002230197,0.003203255,0.004617141,0.0831077,0.02388001,0.06664095,0.7933087,0.0003490101],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0614044,0.02157205,0.7742206,0.007494541,0.001741352,0.0005586953,0.0006370457,0.003771544,0.1285997],"genre_scores_gemma":[0.6311814,0.01708163,0.3081024,0.001277595,0.0007712124,0.0006637362,0.0005127542,0.0002552426,0.04015392],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01546125,"threshold_uncertainty_score":0.051723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06703309815242767,"score_gpt":0.3364246025974358,"score_spread":0.2693915044450081,"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."}}