{"id":"W16696109","doi":"","title":"Autonomous Rover Navigation in Partially Known Terrain","year":2003,"lang":"en","type":"article","venue":"Harvard Heart Letter : From Harvard Medical School","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mobile robot; Terrain; Planner; Computer science; Motion planning; Software; Path (computing); Artificial intelligence; Robot; Real-time computing; Simulation; Engineering; Computer vision; Geography; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001690983,0.0002666113,0.000360035,0.0002190685,0.0003455002,0.0004708479,0.0003912251,0.0004445528,0.0007330358],"category_scores_gemma":[0.0008271238,0.000220277,0.0001717542,0.0002286579,0.0003703769,0.0007817065,0.0005207637,0.0003875533,0.0004763669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001984001,"about_ca_system_score_gemma":0.0003613848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00572392,"about_ca_topic_score_gemma":0.009280899,"domain_scores_codex":[0.999842,0.00002933629,0.000004969931,0.00003230865,0.00006413999,0.00002713753],"domain_scores_gemma":[0.9997823,0.00008131047,0.0000205189,0.00005115843,0.00004695842,0.00001787683],"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":[0.0004507587,0.0000517967,0.00362071,0.000136522,0.00009557411,0.0009069229,0.0004855251,0.5693814,0.05144316,0.02390863,0.01036188,0.339157],"study_design_scores_gemma":[0.000038956,0.0001094048,0.002234687,0.00001447611,0.00001513962,0.0003901465,0.0001586241,0.9627776,0.005255619,0.01196315,0.01702249,0.00001977332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1356445,0.001207597,0.8475947,0.0006780825,0.0001771837,0.00005079322,0.0001660459,0.002421039,0.01206],"genre_scores_gemma":[0.8403022,0.0008038731,0.1514065,0.0001752179,0.00009457966,0.0000531247,0.0003792304,0.0001362502,0.006648865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00572392,"threshold_uncertainty_score":0.01138121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312806912019933,"score_gpt":0.2509311660868707,"score_spread":0.2378030969666714,"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."}}