{"id":"W4252308724","doi":"10.25071/10315/35247","title":"Comparative Analysis Of Optitrack Motion Capture Systems","year":2018,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Christian Studies; University of Toronto","funders":"","keywords":"Computer science; Motion capture; Motion analysis; Motion (physics); Artificial intelligence; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003164598,0.0001438076,0.0004195686,0.0008679078,0.00002640568,0.00003342571,0.0001102974,0.0002127489,0.00003284379],"category_scores_gemma":[0.00002546079,0.0001499401,0.00008172302,0.001433296,0.00001921289,0.00008217661,0.000008629185,0.0002092264,0.00001017106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000308795,"about_ca_system_score_gemma":0.00003434871,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01949501,"about_ca_topic_score_gemma":0.04710162,"domain_scores_codex":[0.9989285,0.00002345256,0.0003680571,0.0001657458,0.0001607547,0.0003535082],"domain_scores_gemma":[0.9994364,0.00003176882,0.00003627501,0.000180865,0.00008232781,0.0002323444],"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":[0.00001603123,0.00002158459,0.002560703,0.0001856301,0.0008511062,0.00002776929,0.0007729288,0.9795359,0.001702314,0.01011213,0.0001550833,0.004058811],"study_design_scores_gemma":[0.0001456707,0.00003165796,0.001708409,0.00007696022,0.000074346,0.000003343888,0.00007597604,0.9936191,0.002321521,0.00000360784,0.001776021,0.0001633921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9359078,0.002508426,0.05289848,0.00003273032,0.004595831,0.0009944609,0.0001303556,0.0004547703,0.002477088],"genre_scores_gemma":[0.9994937,0.000003123506,0.000281898,0.000003235027,0.0001511029,0.00003485619,0.000009398098,0.00001627159,0.000006410514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06358585,"threshold_uncertainty_score":0.9870343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01939986741845149,"score_gpt":0.2543730031196259,"score_spread":0.2349731357011744,"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."}}