{"id":"W1505256789","doi":"10.1109/acssc.1998.750821","title":"Dynamic reconstruction of sea clutter using regularized REP networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Chaos control and synchronization","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Clutter; Dimension (graph theory); Series (stratigraphy); Computer science; Radial basis function; Predictability; Constant false alarm rate; Artificial intelligence; Correlation dimension; Lyapunov exponent; Algorithm; Mathematics; Artificial neural network; Statistics; Mathematical analysis; Radar; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004211334,0.0003361737,0.0002741636,0.0003706812,0.0001397915,0.0003017195,0.0003389236,0.0003475995,0.0004907514],"category_scores_gemma":[0.001782217,0.0001500031,0.0002943265,0.0003179238,0.0003065904,0.0006294994,0.0002911948,0.0003631356,0.0001437041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000295377,"about_ca_system_score_gemma":0.0002016745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002480078,"about_ca_topic_score_gemma":0.001591128,"domain_scores_codex":[0.9998977,0.0000288199,0.000004515054,0.00002170641,0.00002915901,0.00001796673],"domain_scores_gemma":[0.9996861,0.0001200591,0.00006033844,0.00004965118,0.00006955014,0.00001430253],"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":[0.0001075403,0.00001925809,0.001251953,0.00002237854,0.00002139541,0.0001629607,0.00005418533,0.9342996,0.01592502,0.00931036,0.0002237436,0.03860164],"study_design_scores_gemma":[0.000001020865,0.000006988516,0.0001084524,6.749382e-7,0.000001259332,0.00001329641,0.000002118626,0.9979615,0.001023463,0.000816793,0.00006230958,0.000002156627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2778109,0.0001266258,0.7197705,0.0001656482,0.0000225803,0.00001043732,0.00004491999,0.0004346624,0.001613597],"genre_scores_gemma":[0.9514233,0.00009923369,0.04767073,0.0000188344,0.00001117489,0.000008966936,0.00005436588,0.0000302324,0.0006829822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002480078,"threshold_uncertainty_score":0.004931331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008948856597201262,"score_gpt":0.2046886524276769,"score_spread":0.1957397958304757,"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."}}