{"id":"W4286632245","doi":"10.1155/2022/9681455","title":"The Robust Semantic SLAM System for Texture-Less Underground Parking Lot","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer vision; Computer science; Artificial intelligence; Simultaneous localization and mapping; Global Positioning System; Parking lot; Robot; Engineering; Mobile robot","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003297117,0.0006024739,0.0007179299,0.0004889197,0.0003775691,0.000430947,0.000937961,0.0005481719,0.002564396],"category_scores_gemma":[0.0005920914,0.0002871288,0.0004862148,0.0004866602,0.0003024245,0.0009160842,0.001245189,0.0005198036,0.001201258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002517041,"about_ca_system_score_gemma":0.001054856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002897074,"about_ca_topic_score_gemma":0.001980045,"domain_scores_codex":[0.9996589,0.00003584211,0.00001731889,0.00006806868,0.0001660469,0.00005386622],"domain_scores_gemma":[0.9997829,0.0000118473,0.00002417182,0.00006744589,0.00009507223,0.0000185301],"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":[0.0008845304,0.0001587819,0.001988823,0.0004005444,0.0001208672,0.0004037789,0.0003059224,0.1079932,0.2568891,0.005900371,0.017005,0.6079489],"study_design_scores_gemma":[0.0001640012,0.0003415865,0.003468778,0.00001994202,0.00005727081,0.0004057522,0.0001395448,0.9242068,0.05359341,0.003493411,0.01401491,0.00009459909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04706489,0.0001511563,0.9407842,0.00009733275,0.0001596169,0.00007604575,0.0003091347,0.008804346,0.002553313],"genre_scores_gemma":[0.7837865,0.0001169599,0.2112008,0.0001299269,0.00005301437,0.0001369614,0.001074127,0.0001879284,0.003313839],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002897074,"threshold_uncertainty_score":0.008578777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01230774922638352,"score_gpt":0.2089412916941315,"score_spread":0.196633542467748,"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."}}