{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001804231,0.0001132407,0.0001237272,0.0001434403,0.000555877,0.00002349817,0.0001245455,0.00005634276,0.0001054633],"category_scores_gemma":[0.0000281196,0.0001380678,0.0001009985,0.0002947832,0.00002961188,0.00005496739,0.000002934415,0.0003803628,0.000001303114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006321955,"about_ca_system_score_gemma":0.00001813417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007311872,"about_ca_topic_score_gemma":0.000004383155,"domain_scores_codex":[0.999262,0.00004656673,0.0001924081,0.0001677292,0.0001434188,0.000187852],"domain_scores_gemma":[0.9994935,0.0001687201,0.00002497109,0.0002348315,0.00002996664,0.00004795243],"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":[0.00003762442,0.00003183922,0.0002355952,0.00002716252,0.00003018187,9.910935e-7,0.0002488733,0.9915831,0.0005028259,0.0003709113,0.00007628107,0.006854581],"study_design_scores_gemma":[0.001267151,0.0005657758,0.0005013202,0.00002118821,0.00008137531,0.00001816893,0.0009981969,0.9728046,0.001894801,0.005743146,0.0156259,0.0004783727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.219834,0.00003573054,0.7783452,0.0001060961,0.0009621914,0.0002337217,0.00006656464,0.0003094234,0.0001070753],"genre_scores_gemma":[0.9952053,0.00002789666,0.004462038,0.00005055489,0.00004286828,0.00009724556,0.00005340533,0.00003661154,0.00002412415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7753713,"threshold_uncertainty_score":0.5630243,"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."}}