{"id":"W7073543676","doi":"","title":"Autonomous Multi-UAV Path Planning in Pipe Inspection Missions Based on Booby Behavior","year":2023,"lang":"en","type":"article","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Nuclear Structure and Function","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Population and Public Health; King Saud University","keywords":"Heuristic; Motion planning; Ant colony optimization algorithms; Path (computing); Particle swarm optimization; Ant colony","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004412338,0.0004929209,0.0005682904,0.0003298746,0.0005217673,0.0003537062,0.0006078584,0.0004689973,0.0005380605],"category_scores_gemma":[0.0009306095,0.0003778751,0.0002617333,0.0001818606,0.0006391098,0.0005219001,0.0005610174,0.0003954854,0.00008092788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003849513,"about_ca_system_score_gemma":0.0008423794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004761401,"about_ca_topic_score_gemma":0.004081356,"domain_scores_codex":[0.9998291,0.00004947369,0.000006732879,0.00003587917,0.00004625082,0.00003269356],"domain_scores_gemma":[0.9996294,0.0001848422,0.00007211074,0.00002955896,0.00004189325,0.00004215873],"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":[0.0001122623,0.00005299845,0.001362322,0.00007066929,0.00003113578,0.0001244632,0.0001120537,0.9378855,0.01094732,0.003240783,0.0003291557,0.04573149],"study_design_scores_gemma":[0.00001196554,0.0001119051,0.0003392419,0.000006715679,0.000007197407,0.00005022447,0.00003153126,0.9961826,0.001752825,0.000935979,0.00056174,0.000007978026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09090474,0.0002889824,0.9062659,0.00009055452,0.00003001698,0.00008693822,0.00001412533,0.000342134,0.001976534],"genre_scores_gemma":[0.8714974,0.0001127189,0.1276278,0.00003136687,0.000006694429,0.00007174513,0.00001757895,0.00003207001,0.0006027127],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004761401,"threshold_uncertainty_score":0.009467363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01606007576360481,"score_gpt":0.2681411648331604,"score_spread":0.2520810890695556,"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."}}