{"id":"W4309679509","doi":"10.1109/smc53654.2022.9945496","title":"Evolutionary Mapping with Multiple Unmanned Aerial Vehicles","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Drone; Computer science; Context (archaeology); Motion planning; Obstacle; Plan (archaeology); Real-time computing; Search and rescue; Evolutionary algorithm; Operations research; Artificial intelligence; Robot; Engineering","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":[0.0006032314,0.0008182232,0.0006192857,0.000659405,0.0005172167,0.0005402618,0.0009470076,0.0007122312,0.001197395],"category_scores_gemma":[0.001097279,0.0003511339,0.0006969602,0.0006248421,0.0003586325,0.0006852741,0.0009751088,0.0005989498,0.0001274347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005085357,"about_ca_system_score_gemma":0.0005847592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005299863,"about_ca_topic_score_gemma":0.004019081,"domain_scores_codex":[0.9995944,0.000122138,0.00001625181,0.00007961818,0.0001359659,0.00005171711],"domain_scores_gemma":[0.9996905,0.0001321605,0.00004976289,0.0000393201,0.0000633462,0.00002476796],"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":[0.00003005959,0.00004727491,0.000601707,0.00003834746,0.00005270539,0.00009090135,0.00006395222,0.9128588,0.00277948,0.002735329,0.00032041,0.08038097],"study_design_scores_gemma":[0.000008704744,0.00004459122,0.0001938932,0.00000475651,0.000007504931,0.00002769638,0.00001507941,0.9965874,0.000913632,0.001026332,0.001165766,0.000004753876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0854007,0.0004938141,0.9085125,0.000205042,0.00007890357,0.00009770432,0.00003566607,0.0005267142,0.004649064],"genre_scores_gemma":[0.6150333,0.000252179,0.380472,0.00008868885,0.00002590427,0.0002107821,0.00007776111,0.00004741173,0.003791974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005299863,"threshold_uncertainty_score":0.01053804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04777489517899604,"score_gpt":0.2558853031340413,"score_spread":0.2081104079550453,"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."}}