{"id":"W2110647704","doi":"10.1109/iros.2009.5354819","title":"Reliable and intuitive teleoperation of LineScout: a mobile robot for live transmission line maintenance","year":2009,"lang":"en","type":"article","venue":"","topic":"Power Line Inspection Robots","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Teleoperation; Computer science; Robot; Robustness (evolution); Obstacle; Mobile robot; Workload; Robotics; Situation awareness; Embedded system; Real-time computing; Human–computer interaction; Artificial intelligence; Engineering; Operating system","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":[0.0001045294,0.0003642763,0.000211175,0.0001803849,0.0002161838,0.0003201218,0.0005492041,0.0005107392,0.003209836],"category_scores_gemma":[0.000302274,0.0001398466,0.0001257195,0.00007634212,0.000392138,0.0005229212,0.0004617361,0.0003779125,0.0007535237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000114954,"about_ca_system_score_gemma":0.0001686016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003494831,"about_ca_topic_score_gemma":0.0005024878,"domain_scores_codex":[0.9999129,0.00001067037,0.00000294855,0.00002427821,0.00003705896,0.00001214198],"domain_scores_gemma":[0.999902,0.0000199789,0.00001948986,0.00001925209,0.0000192052,0.00001995212],"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":[0.0005279414,0.0001467653,0.000965627,0.0002088785,0.00002034808,0.001178238,0.0006111185,0.01278857,0.6126084,0.004999982,0.007279261,0.3586649],"study_design_scores_gemma":[0.0003663053,0.005934556,0.01264694,0.0001204322,0.00008008695,0.007359039,0.0004932797,0.4745828,0.3137063,0.004600081,0.1799258,0.0001844511],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2186873,0.0004137495,0.7588051,0.00051566,0.0002149128,0.0002853281,0.000116156,0.007233528,0.01372825],"genre_scores_gemma":[0.7848763,0.0002299385,0.1969291,0.000121329,0.00006232231,0.000162667,0.0001312491,0.0002113192,0.01727581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003209836,"threshold_uncertainty_score":0.01073796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006592527461711943,"score_gpt":0.2309885633587224,"score_spread":0.2243960358970104,"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."}}