{"id":"W4311806088","doi":"10.1145/3550454.3555433","title":"Learning Reconstructability for Drone Aerial Path Planning","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Drone; Artificial intelligence; Motion planning; Viewpoints; Computer vision; Heuristic; Path (computing); Planner; 3D reconstruction; Set (abstract data type); Proxy (statistics); Machine learning; Robot","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":[0.0006552385,0.000922199,0.0007995127,0.0005990437,0.0003255628,0.0007320034,0.001165315,0.0008284343,0.001582683],"category_scores_gemma":[0.004735787,0.0005899767,0.0004480234,0.0004211357,0.0009930156,0.001340688,0.001206329,0.001632895,0.000231104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001303497,"about_ca_system_score_gemma":0.001274939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009612951,"about_ca_topic_score_gemma":0.01084424,"domain_scores_codex":[0.9996442,0.00006558414,0.00001609387,0.0001133267,0.0001121726,0.00004871513],"domain_scores_gemma":[0.9985228,0.0008418875,0.0002156988,0.0001460877,0.0001875531,0.00008591793],"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":[0.00002923342,0.00001406081,0.0007178236,0.00001483182,0.00000970158,0.00001753056,0.00001547502,0.980472,0.0007133272,0.001375272,0.0002150257,0.01640563],"study_design_scores_gemma":[0.000002090097,0.00001153834,0.00007409986,0.000001702264,0.000001244986,0.000003890498,0.000001933419,0.9986246,0.0003614364,0.0008416686,0.00007425897,0.000001547012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04106111,0.0001593835,0.9562979,0.0001416876,0.00001470311,0.00004158143,0.0001342153,0.001123661,0.001025845],"genre_scores_gemma":[0.8545312,0.0001678262,0.1428995,0.0000885636,0.00002832834,0.0001021015,0.0004966738,0.0001857785,0.001500119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009612951,"threshold_uncertainty_score":0.01911402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01866540101776537,"score_gpt":0.2284969112575112,"score_spread":0.2098315102397458,"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."}}