{"id":"W2157490622","doi":"10.1109/ccece.2008.4564669","title":"Comparing global measures of image similarity for use in topological localization of mobile robots","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Artificial intelligence; Similarity (geometry); Mobile robot; Computer vision; Robot; Computer science; Image (mathematics); Filter (signal processing); Topology (electrical circuits); Pattern recognition (psychology); Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003505004,0.0008850616,0.001305646,0.006858881,0.0005993065,0.00233105,0.0008987915,0.001039932,0.001428862],"category_scores_gemma":[0.02107523,0.0002532551,0.0007541818,0.003576268,0.001249526,0.003983954,0.001899941,0.0007921298,0.0004552972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006630595,"about_ca_system_score_gemma":0.0004498151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006330798,"about_ca_topic_score_gemma":0.0006703978,"domain_scores_codex":[0.9970732,0.0009018888,0.0002072578,0.0004129483,0.001208373,0.0001963934],"domain_scores_gemma":[0.9869893,0.006026558,0.001731742,0.001562672,0.003193461,0.0004962162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002574204,0.0003913951,0.04682898,0.001219887,0.001025488,0.0005182651,0.001191157,0.06663564,0.0839356,0.0207304,0.002827178,0.7721219],"study_design_scores_gemma":[0.0003161663,0.00711558,0.1710117,0.0004260682,0.001103655,0.003590413,0.003639938,0.5853684,0.1495067,0.06414514,0.01313931,0.0006369131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2547619,0.002028528,0.7366429,0.0001511072,0.0001715132,0.0002141067,0.0002860767,0.0008675937,0.004876163],"genre_scores_gemma":[0.8755875,0.0004845476,0.1223385,0.00005983481,0.00008772305,0.0001470069,0.000553178,0.0001943157,0.000547479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006858881,"threshold_uncertainty_score":0.01853645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04794212203555914,"score_gpt":0.2171629338771079,"score_spread":0.1692208118415488,"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."}}