{"id":"W4410501619","doi":"10.3390/drones9050380","title":"Collision Detection and Recovery Control of Drones Using Onboard Inertial Measurement Unit","year":2025,"lang":"en","type":"article","venue":"Drones","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drone; Inertial measurement unit; Computer science; Collision; Aeronautics; Aerospace engineering; Real-time computing; Engineering; Computer security; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004253043,0.00009966103,0.000189463,0.0001706686,0.0001043237,0.00005025826,0.0001917114,0.00006001428,6.761047e-7],"category_scores_gemma":[0.0001148972,0.00009483005,0.00003066967,0.0002994582,0.00003948512,0.000209698,0.00008610227,0.00006772659,0.000001454565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006010928,"about_ca_system_score_gemma":0.00007964156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001927534,"about_ca_topic_score_gemma":0.0000109687,"domain_scores_codex":[0.9990439,0.00008715757,0.0002227408,0.0002279246,0.0002732496,0.0001450027],"domain_scores_gemma":[0.9994336,0.00007902116,0.00007274876,0.00023347,0.0001476597,0.00003351535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002014648,0.0001947267,0.008682908,0.0002003914,0.0002074577,0.00002208617,0.0007197298,0.09370627,0.7449954,0.002334707,0.0001118382,0.1486231],"study_design_scores_gemma":[0.001042494,0.0001600023,0.01579535,0.0002286984,0.00004199594,0.00001135462,0.00004179068,0.8959476,0.08544529,0.000947057,0.0001773067,0.0001610233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2422323,0.0003145706,0.7564666,0.0001443503,0.0006012592,0.0001210259,0.000001467075,0.00004645438,0.00007194273],"genre_scores_gemma":[0.9672683,0.0000108571,0.03258966,0.00005291033,0.00003389315,0.000005266732,3.644385e-7,0.000004243735,0.00003442991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8022414,"threshold_uncertainty_score":0.3867057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02862949418896979,"score_gpt":0.2545705690277474,"score_spread":0.2259410748387776,"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."}}