{"id":"W2049496251","doi":"10.1108/01439910810868570","title":"Mobile robot localization in quasi‐dynamic environments","year":2008,"lang":"en","type":"article","venue":"Industrial Robot the international journal of robotics research and application","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Mobile robot; Computer science; Robot; Robustness (evolution); Grid; Motion planning; Grid reference; Service robot; Mobile service; Artificial intelligence; Real-time computing; Distributed computing; Service (business)","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":[0.0008065335,0.0001255562,0.0001734999,0.0003508535,0.000132737,0.00007588974,0.0004659507,0.0001461749,0.000008976976],"category_scores_gemma":[0.0001122299,0.0001030057,0.00004499431,0.0003509937,0.0001769743,0.0001924684,0.0000634198,0.0005904521,0.00001235598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003254683,"about_ca_system_score_gemma":0.00007617713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003393982,"about_ca_topic_score_gemma":0.00002071809,"domain_scores_codex":[0.998037,0.00009810792,0.0005647402,0.0001434776,0.000922669,0.0002339897],"domain_scores_gemma":[0.9991614,0.0001904588,0.0001339558,0.0001663383,0.0002458369,0.0001020492],"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":[0.00006456372,0.0001199475,0.001253184,0.000003515971,0.00003831685,0.0000163401,0.0001676749,0.9820507,0.00565616,0.0004552339,0.0006062527,0.009568141],"study_design_scores_gemma":[0.001287824,0.0002736864,0.0007907085,0.00006197362,0.000009148915,0.0001152112,0.0001874223,0.9874497,0.002396053,0.001474624,0.005809394,0.0001442315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07457834,0.0006058717,0.922136,0.001258083,0.0006150575,0.0006032839,0.000006829181,0.00002314756,0.0001733717],"genre_scores_gemma":[0.9959689,0.002767702,0.0007290736,0.00003523753,0.0003256853,0.00002120427,0.00002768806,0.0000251039,0.00009944275],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9214069,"threshold_uncertainty_score":0.4200449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05596178558275277,"score_gpt":0.3127977560158407,"score_spread":0.2568359704330879,"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."}}