{"id":"W4376606508","doi":"10.1109/aero55745.2023.10115826","title":"Transfer Learning for Hypersonic Vehicle Trajectory Prediction","year":2023,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"Lockheed Martin","keywords":"Trajectory; Computer science; Transfer of learning; Artificial intelligence; Hypersonic speed; Machine learning; Aerospace engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001234286,0.00004538318,0.00004550412,0.00006941424,0.0001831539,0.00003442935,0.0001634386,0.00003583222,0.0000150276],"category_scores_gemma":[0.000004833752,0.00004307003,0.00005594463,0.0003773189,0.000010122,0.0002012845,0.00001589013,0.00006116844,0.00006451412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001597406,"about_ca_system_score_gemma":0.00001485189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007599869,"about_ca_topic_score_gemma":0.000001687001,"domain_scores_codex":[0.9995348,0.000009947263,0.00008316759,0.0001779241,0.00006652881,0.0001276326],"domain_scores_gemma":[0.999765,0.00003921817,0.000007737027,0.0001316523,0.00002536457,0.00003099921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001238578,0.0000878701,0.000918793,0.00004396881,0.00003515351,0.000001451188,0.001049262,0.005839268,0.1858373,0.3345361,0.01564448,0.4559939],"study_design_scores_gemma":[0.000267446,0.0002205559,0.00434579,0.000004365468,0.000005454338,0.000003778542,0.0001240729,0.8108361,0.05844209,0.00227611,0.1233371,0.0001371214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05316801,0.000006392506,0.9422659,0.0006495656,0.00005596397,0.0001855569,0.000001038664,0.002090329,0.001577247],"genre_scores_gemma":[0.9873091,0.0000166671,0.007844163,0.000115165,0.0000467633,0.0002548861,0.000003793994,0.000007211542,0.004402261],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9344217,"threshold_uncertainty_score":0.1756345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02211579687514478,"score_gpt":0.2469380071966197,"score_spread":0.2248222103214749,"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."}}