{"id":"W2901106272","doi":"10.1155/2018/2964583","title":"Design of Fully Automatic Drone Parachute System with Temperature Compensation Mechanism for Civilian and Military Applications","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Aerospace Engineering and Energy Systems","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Fahd University of Petroleum and Minerals","keywords":"Drone; Accelerometer; Compensation (psychology); Kalman filter; Gyroscope; Acceleration; Mechanism (biology); Computer science; Aeronautics; Simulation; Automotive engineering; Engineering; Aerospace engineering; Real-time computing; Computer security; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001259459,0.0001047006,0.0002141528,0.00007576244,0.00004241948,0.000004826635,0.00004601594,0.00005456,6.330619e-7],"category_scores_gemma":[0.000002568272,0.00008958744,0.00002917106,0.000109489,0.00002068824,0.0001865559,3.29197e-7,0.00006584769,2.408735e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003699105,"about_ca_system_score_gemma":0.0000160528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003337436,"about_ca_topic_score_gemma":0.00003246301,"domain_scores_codex":[0.9993519,0.000009930584,0.0003518743,0.00007072456,0.0001240926,0.00009151282],"domain_scores_gemma":[0.9994742,0.00003779179,0.0001276,0.00007988573,0.0002327084,0.00004785578],"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":[0.000062577,0.00001009168,0.0000179254,0.0006154957,0.00007839272,0.000001394569,0.001006725,0.9073172,0.08882807,0.001392145,0.00001357805,0.0006564666],"study_design_scores_gemma":[0.00619923,0.003635786,0.02264253,0.002955914,0.0006618386,0.0002079739,0.007342296,0.8559238,0.09841643,0.0008078921,0.000306646,0.0008996446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3416851,0.0002099458,0.6577066,0.00001290759,0.0001097617,0.0002159448,0.00000988737,0.00004626868,0.000003591662],"genre_scores_gemma":[0.9122925,0.00003639424,0.08749904,0.000002371036,0.00008759942,0.00003809814,0.00001493294,0.00002216958,0.000006939169],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5706074,"threshold_uncertainty_score":0.365327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004938777217384859,"score_gpt":0.1886783178487956,"score_spread":0.1837395406314107,"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."}}