{"id":"W2150690788","doi":"10.1109/iros.1998.727278","title":"A nonparametric learning approach to vision based mobile robot localization","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Artificial intelligence; Computer vision; Workspace; Mobile robot; Computer science; Robot; Pixel; Nonparametric statistics; Robotics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001298085,0.0006796404,0.0009340246,0.0010099,0.0004117291,0.0009232809,0.001431366,0.001027975,0.001170522],"category_scores_gemma":[0.004659964,0.0003934113,0.0007065008,0.001228622,0.001449715,0.001020616,0.001106156,0.001247048,0.0004290577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008087908,"about_ca_system_score_gemma":0.0007238749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002552636,"about_ca_topic_score_gemma":0.001650525,"domain_scores_codex":[0.999126,0.0003298938,0.00003602816,0.000173749,0.000274032,0.00006033789],"domain_scores_gemma":[0.9984013,0.0009737565,0.0001592446,0.0001877434,0.0002469747,0.00003089666],"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":[0.00006096982,0.00006139301,0.0005834714,0.000139243,0.00007904066,0.0001226782,0.00008468567,0.7784615,0.003622473,0.04940619,0.001176578,0.1662018],"study_design_scores_gemma":[0.000005687252,0.00003603684,0.0001527207,0.000006636737,0.000006313522,0.00004120508,0.000006533034,0.9792784,0.0005952907,0.0188228,0.001038327,0.000009900107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008741583,0.00008400671,0.998566,0.00004148644,0.000008931971,0.000007036029,0.000007899302,0.00008201821,0.0003285779],"genre_scores_gemma":[0.4411545,0.000712165,0.5527584,0.0001831042,0.0003204639,0.0004027871,0.0001942457,0.0001102591,0.004164061],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002552636,"threshold_uncertainty_score":0.006865025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230645488497768,"score_gpt":0.2078790835946271,"score_spread":0.1955726287096495,"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."}}