{"id":"W4319241313","doi":"10.36227/techrxiv.21432012.v2","title":"Human-as-a-Robot Performance in Augmented Reality Teleultrasound","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Teleoperation; Rendering (computer graphics); Computer science; Augmented reality; Computer vision; Human motion; Artificial intelligence; Simulation; Robot; Motion (physics)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009636748,0.0003912875,0.0004402765,0.0003713092,0.0002201717,0.0002884422,0.00296174,0.0003950078,0.00006400376],"category_scores_gemma":[0.00005519002,0.0003981701,0.0001349738,0.0008801341,0.0001232073,0.000267607,0.003159636,0.001128411,0.0008091197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004642588,"about_ca_system_score_gemma":0.0003048056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003622017,"about_ca_topic_score_gemma":0.001411768,"domain_scores_codex":[0.9965583,0.0001389448,0.0008025935,0.001330883,0.0006074936,0.0005617868],"domain_scores_gemma":[0.9966491,0.0001287719,0.0003020131,0.002649405,0.0001172749,0.0001533929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002590696,0.002453357,0.02060269,0.001917546,0.0005240334,0.0001326436,0.004597173,0.1857697,0.004129665,0.7067988,0.04228801,0.0307605],"study_design_scores_gemma":[0.001604932,0.0001944591,0.5552274,0.0008934042,0.00005814686,0.00005014824,0.0002808751,0.2653818,0.004412277,0.1580783,0.01105245,0.002765796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0903169,0.00005429092,0.8304871,0.01097657,0.0009681014,0.002455551,0.00005929362,0.003272881,0.06140926],"genre_scores_gemma":[0.9809731,0.0001655288,0.007919754,0.0004050453,0.000104367,0.00074733,0.0002225303,0.00004493,0.009417452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8906562,"threshold_uncertainty_score":0.9999689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08400588472076077,"score_gpt":0.3458913109439105,"score_spread":0.2618854262231498,"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."}}