{"id":"W1937997142","doi":"10.1109/iros.1996.568966","title":"Fuzzy matching for robot localization","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Landmark; Artificial intelligence; Robot; Computer vision; Robustness (evolution); Computer science; Fuzzy logic; Mobile robot; Matching (statistics); Pattern matching; Mobile robot navigation; Pattern recognition (psychology); Robot control; Mathematics","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":[0.00003216101,0.00007026882,0.00006739851,0.00004100597,0.0000489363,0.00003161289,0.00003823659,0.00004527117,0.0001240174],"category_scores_gemma":[0.000007670415,0.00006890635,0.00002831673,0.00008708769,0.000005100359,0.00006806399,0.000003412822,0.00002665911,0.00005213864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002312781,"about_ca_system_score_gemma":9.147564e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005156685,"about_ca_topic_score_gemma":0.000007836319,"domain_scores_codex":[0.9996136,0.000004122031,0.0001198771,0.00007630269,0.00006133477,0.000124739],"domain_scores_gemma":[0.9998236,0.00002107225,0.000008774242,0.00008653018,0.00002668047,0.00003334362],"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":[5.542576e-7,0.000006938281,0.00002865176,0.00002977048,0.000005773657,2.760591e-7,0.00007239347,0.9811942,0.0005922561,0.00981334,0.005439028,0.002816844],"study_design_scores_gemma":[0.0001581638,0.00001112311,0.00001937844,0.000007185322,0.000005781868,8.87538e-7,0.00002109313,0.9923402,0.001373495,0.001824467,0.004138632,0.00009959599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009390766,0.00007689042,0.9801593,0.0000747411,0.0001947863,0.0001214719,0.000001613364,0.0002922516,0.0181398],"genre_scores_gemma":[0.9861222,0.00004541058,0.01269377,0.0001683499,0.00009182753,0.000009738135,0.00002581056,0.00003399403,0.0008089055],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9851831,"threshold_uncertainty_score":0.2809919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01902972100090592,"score_gpt":0.2033708009009754,"score_spread":0.1843410799000695,"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."}}