{"id":"W2069552341","doi":"10.1016/j.cviu.2009.06.010","title":"Visual search for an object in a 3D environment using a mobile robot","year":2010,"lang":"en","type":"article","venue":"Computer Vision and Image Understanding","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Artificial intelligence; Object (grammar); Limit (mathematics); Mobile robot; Robot; Computer vision; Visual search; Space (punctuation); Optimization problem; Mechanism (biology); Mathematics; Algorithm","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":[0.0006404269,0.000140856,0.0001619661,0.0002790088,0.0002601445,0.0006074772,0.0002818386,0.00006560025,0.00002213303],"category_scores_gemma":[0.000005108719,0.0001292612,0.00003785894,0.0001966209,0.00008864194,0.0009400735,0.0003222142,0.0002152997,0.000003684743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035025,"about_ca_system_score_gemma":0.00004643123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001237704,"about_ca_topic_score_gemma":0.000008822469,"domain_scores_codex":[0.9986675,0.00008447968,0.0002126932,0.0004696496,0.0002231074,0.0003425707],"domain_scores_gemma":[0.999411,0.0001054709,0.00003892561,0.0002465937,0.0000284176,0.0001695342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002238505,0.001997342,0.002230833,0.0003414072,0.00006418948,0.0001018014,0.01738728,0.1010806,0.435396,0.0872547,0.0005285077,0.3533936],"study_design_scores_gemma":[0.0008467515,0.0005229365,0.0001468541,0.00002725889,0.000001603572,0.00001811186,0.0001543388,0.9964576,0.0005714523,0.0008988563,0.0001860565,0.0001681412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03720071,0.00001563198,0.9618695,0.0001067393,0.0001754285,0.0004840307,0.000001211425,0.00005800524,0.00008870682],"genre_scores_gemma":[0.5156657,0.00001628799,0.4841189,0.0001152888,0.00004750441,0.000009426366,0.000003503107,0.00001090777,0.00001249054],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.895377,"threshold_uncertainty_score":0.5857916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06650966170180576,"score_gpt":0.3477666385531639,"score_spread":0.2812569768513581,"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."}}