{"id":"W4394626915","doi":"10.23977/jeis.2024.090116","title":"Radar recognition system based on XG-Boost","year":2024,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Xijing University","keywords":"Computer science; Radar; Artificial intelligence; Aeronautics; Engineering; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003846104,0.0003859403,0.0005801509,0.0004691303,0.0003224906,0.0005958013,0.0008113764,0.0004456377,0.004415633],"category_scores_gemma":[0.0003918213,0.0001937352,0.0002841964,0.0003686467,0.0001974087,0.0005868216,0.0004604826,0.0005154008,0.00264588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002769505,"about_ca_system_score_gemma":0.0004227037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001759884,"about_ca_topic_score_gemma":0.001091317,"domain_scores_codex":[0.9996973,0.00002378818,0.00001774706,0.00007469569,0.0001451221,0.00004129969],"domain_scores_gemma":[0.9997872,0.00002003074,0.00002086532,0.00003211587,0.0001209306,0.00001893476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009910723,0.0002144736,0.005146882,0.0004598807,0.0001204343,0.0005991817,0.0001686125,0.03441793,0.2294789,0.005255104,0.02272548,0.700422],"study_design_scores_gemma":[0.0001803112,0.0007017595,0.008869325,0.0000567738,0.0001593605,0.001394574,0.00005932397,0.7056719,0.2471564,0.002428812,0.03319921,0.0001221286],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07683349,0.001102797,0.8781647,0.0004246067,0.0005324877,0.0002255235,0.0003022434,0.01668691,0.02572723],"genre_scores_gemma":[0.8176984,0.0006989939,0.1539234,0.0007558196,0.0001593382,0.0001546903,0.000673789,0.0001676784,0.02576783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004415633,"threshold_uncertainty_score":0.01477176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00474181820938087,"score_gpt":0.2023088784747802,"score_spread":0.1975670602653993,"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."}}