{"id":"W2128677896","doi":"10.1109/robot.2001.933198","title":"Map building for a terrain scanning robot","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer vision; Terrain; Artificial intelligence; Robot; Computer science; Mobile robot; Motion planning; Obstacle; Obstacle avoidance; Geography","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":[0.0001023324,0.0005704826,0.0002668888,0.0003911438,0.0004776022,0.0004355025,0.000729915,0.0006651287,0.008556696],"category_scores_gemma":[0.0002785008,0.0003686726,0.0004173582,0.000270959,0.0003111526,0.0006129745,0.0005260978,0.0006644109,0.003906603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002587484,"about_ca_system_score_gemma":0.0003428181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002010549,"about_ca_topic_score_gemma":0.002221694,"domain_scores_codex":[0.9999132,0.0000130568,0.000003756802,0.00001848939,0.00003983043,0.00001157721],"domain_scores_gemma":[0.9999371,0.00001615798,0.00000471516,0.00001477996,0.00001789838,0.000009340881],"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":[0.0001884204,0.0001169723,0.0009746687,0.0005125955,0.00007404977,0.0008432014,0.0005055555,0.06744774,0.1386188,0.05583228,0.02200013,0.7128854],"study_design_scores_gemma":[0.00007721757,0.0003087507,0.001246432,0.00006789646,0.00006588833,0.001368623,0.0001368674,0.5811405,0.09885798,0.02778417,0.2888593,0.00008629372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005314213,0.000226151,0.978962,0.0001767124,0.00009378613,0.00005998552,0.00008795196,0.007119539,0.007959553],"genre_scores_gemma":[0.09181358,0.0004104929,0.892857,0.00008553175,0.00005753414,0.0001600174,0.0003240214,0.0004150117,0.01387688],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008556696,"threshold_uncertainty_score":0.02862501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973398831479585,"score_gpt":0.2180397964211517,"score_spread":0.1983058081063558,"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."}}