{"id":"W3133367930","doi":"10.1016/j.ohx.2021.e00179","title":"Design and validation of an inertial measurement unit (IMU)-based sensor for capturing camera movement in the operating room","year":2021,"lang":"en","type":"article","venue":"HardwareX","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"Royal College of Physicians and Surgeons of Canada","keywords":"Inertial measurement unit; Computer vision; Computer science; Wearable computer; Artifact (error); Artificial intelligence; Video camera; Microcontroller; Units of measurement; Motion capture; Motion (physics); Computer hardware; Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009784426,0.00007897923,0.00009812806,0.00004387179,0.0001109447,0.000100913,0.0002499144,0.00002657798,0.00000294888],"category_scores_gemma":[0.00007735416,0.00006574194,0.00002132592,0.0001989492,0.00001466087,0.0001277154,0.00005172915,0.00006095057,6.00701e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005107034,"about_ca_system_score_gemma":0.0001379763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001132935,"about_ca_topic_score_gemma":0.00005634966,"domain_scores_codex":[0.9988626,0.0002318003,0.0002276795,0.000241434,0.0003059698,0.0001305516],"domain_scores_gemma":[0.9992192,0.0001097147,0.00007423642,0.0003719798,0.0001932761,0.00003157442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002286165,0.0005469971,0.0006717002,0.0001185396,0.00004795808,0.00001142528,0.007787491,0.5512837,0.4140297,0.007141429,0.0001474897,0.01819067],"study_design_scores_gemma":[0.0005744415,0.00005573709,0.001214105,0.00003572693,0.00001055795,0.000001980967,0.000397787,0.5453808,0.4517991,0.0002674006,0.0001723854,0.00008997181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08629148,0.00003146534,0.9116375,0.001421846,0.00002652862,0.0005343488,0.000004256272,0.00002071464,0.00003187034],"genre_scores_gemma":[0.9117293,0.000001638127,0.08759432,0.0004629571,0.00002221351,0.0001613542,0.00001687124,0.000005662382,0.000005695018],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8254378,"threshold_uncertainty_score":0.2680879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08261710748821617,"score_gpt":0.2841807007791292,"score_spread":0.2015635932909131,"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."}}