{"id":"W3008322647","doi":"10.1117/12.2546483","title":"Augmented reality and human factors regarding the neurosurgical operating room workflow","year":2020,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Augmented reality; Workflow; Computer science; Human–computer interaction; Field (mathematics); Interface (matter); Virtual reality; Usability","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":[0.003250316,0.0003583937,0.0001628555,0.0008157013,0.001009114,0.006134986,0.0003943859,0.0006198174,0.00389792],"category_scores_gemma":[0.01497562,0.0001958306,0.0003620283,0.0006459727,0.001587567,0.001328625,0.00137281,0.0005234954,0.0004783616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001016258,"about_ca_system_score_gemma":0.001811374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006742933,"about_ca_topic_score_gemma":0.005163862,"domain_scores_codex":[0.9959664,0.002423474,0.0002197518,0.0003354778,0.0007492406,0.0003055774],"domain_scores_gemma":[0.9881992,0.007518474,0.001824162,0.0004035397,0.001239572,0.0008150147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00141057,0.0009186979,0.2207951,0.002128629,0.0003926317,0.002226382,0.1847826,0.01976152,0.01857001,0.04417857,0.01320942,0.4916257],"study_design_scores_gemma":[0.0001296984,0.002340963,0.5615199,0.001816762,0.0004576058,0.002924481,0.230864,0.03643315,0.005778865,0.04158013,0.1153498,0.0008046181],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8674054,0.004956331,0.06129497,0.007161951,0.0003277705,0.0002382167,0.0003217439,0.0003547615,0.05793887],"genre_scores_gemma":[0.9908375,0.0009679479,0.006406503,0.0001544647,0.00003069157,0.00004791312,0.00005133807,0.00002620235,0.001477364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006742933,"threshold_uncertainty_score":0.0171895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05968230299874775,"score_gpt":0.2901735827815971,"score_spread":0.2304912797828493,"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."}}