{"id":"W2054526672","doi":"10.1117/12.781499","title":"A hardware neural network for target tracking","year":2008,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Computer science; Artificial neural network; IBM; Tracking (education); Set (abstract data type); Computer hardware; Energy (signal processing); Parallel computing; Algorithm; Artificial intelligence","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":[0.0003715604,0.0002898403,0.0003746471,0.00005507296,0.0002575263,0.0001517092,0.001764579,0.0001403103,0.000003854171],"category_scores_gemma":[0.0001964511,0.0002440427,0.0007155622,0.0004666614,0.0001645712,0.0008167165,0.0002381641,0.0002702029,0.000001027459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007417456,"about_ca_system_score_gemma":0.00002820003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003744916,"about_ca_topic_score_gemma":8.497071e-8,"domain_scores_codex":[0.9978629,1.064076e-8,0.0006095123,0.0004808264,0.0005194317,0.0005273212],"domain_scores_gemma":[0.9978297,0.0002072917,0.0003556446,0.00009017799,0.001379791,0.0001374422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003783915,0.00009967028,0.0004574764,0.0001825343,0.0001896389,1.500296e-7,0.0001931306,0.003296219,0.08281748,0.8845164,0.02743674,0.0007727596],"study_design_scores_gemma":[0.001668137,0.0005193001,0.00228664,0.0002842515,0.0001074692,0.00009502692,0.0002557815,0.8832488,0.05756229,0.01434771,0.03881681,0.000807774],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9874866,0.0001535719,0.005274379,0.005115191,0.0003500365,0.0007809104,0.00003438779,0.0001690177,0.000635916],"genre_scores_gemma":[0.4063606,0.00008294864,0.5912125,0.0003714215,0.001199178,0.0004397396,0.00001066598,0.00005641735,0.0002664941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8799526,"threshold_uncertainty_score":0.9951772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01832339192756081,"score_gpt":0.2333335120211452,"score_spread":0.2150101200935844,"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."}}