{"id":"W2078048554","doi":"10.1117/12.881520","title":"Safeguarding teleoperation using automotive radar sensors","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Teleoperation; Automotive industry; Reliability (semiconductor); Radar; Automotive engineering; Ground-penetrating radar; Unmanned ground vehicle; Service (business); Single point of failure; Simulation; Robot; Embedded system; Systems engineering; Real-time computing; Aerospace engineering; Telecommunications; Artificial intelligence; Engineering; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005373323,0.0003612216,0.0004533155,0.0001483201,0.0001112184,0.0001121486,0.0005721737,0.0002209751,0.00003930289],"category_scores_gemma":[0.0002689234,0.0003192384,0.0004951108,0.0003350989,0.0001215439,0.0007039001,0.00007457542,0.0002879619,0.000004386204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002369883,"about_ca_system_score_gemma":0.00002860184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001778169,"about_ca_topic_score_gemma":2.919845e-7,"domain_scores_codex":[0.9978952,2.051924e-8,0.0008069749,0.0003263349,0.0005641406,0.0004073598],"domain_scores_gemma":[0.9981337,0.00006840754,0.0002132333,0.00006566057,0.001389321,0.0001297065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004231432,0.00006925256,0.0003470559,0.0004534068,0.0006008819,2.071624e-7,0.001605607,0.00206198,0.7352474,0.2576357,0.001680088,0.0002560816],"study_design_scores_gemma":[0.001499511,0.0002672265,0.00146864,0.000534346,0.0002762138,0.00007314495,0.005983766,0.4469428,0.5387521,0.0004851264,0.002870924,0.0008462264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902837,0.00009018646,0.0003083943,0.0002003857,0.0005763886,0.0005604451,0.00003162357,0.0002746113,0.007674226],"genre_scores_gemma":[0.8695757,0.0000547238,0.1294904,0.00004831047,0.0004988062,0.0000706331,0.000006381913,0.00009913021,0.0001559603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4448808,"threshold_uncertainty_score":0.999926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01980458852270819,"score_gpt":0.2224005867359699,"score_spread":0.2025959982132617,"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."}}