{"id":"W2348148951","doi":"","title":"Underwater Target Fusion Recognition Based on Non-linear Dimensionality Reduction","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dimensionality reduction; Computer science; Artificial intelligence; Pattern recognition (psychology); Underwater; Classifier (UML); Support vector machine; Computation; Curse of dimensionality; Feature vector; Algorithm","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":[0.0005975048,0.0003898647,0.0008321746,0.0006431873,0.0003097384,0.0005416762,0.0004434961,0.0003151345,0.0006620144],"category_scores_gemma":[0.001644401,0.000223528,0.0004490774,0.0005916838,0.000356883,0.001269229,0.0006053025,0.000503655,0.0004219741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002228035,"about_ca_system_score_gemma":0.0003352715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00067407,"about_ca_topic_score_gemma":0.0007675231,"domain_scores_codex":[0.9991968,0.0001238134,0.00004984274,0.0001343108,0.0004448073,0.00005045649],"domain_scores_gemma":[0.9994406,0.0001775064,0.00006274962,0.00008805381,0.000213865,0.00001721858],"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":[0.0002018471,0.0001165914,0.002062986,0.0001426756,0.00007907213,0.00009309167,0.0001904337,0.03195765,0.200232,0.006400361,0.001618891,0.7569044],"study_design_scores_gemma":[0.0000210915,0.0001739813,0.003065671,0.00000833988,0.00003572713,0.0003337887,0.00005405498,0.8656576,0.1238839,0.003526041,0.003197985,0.00004176416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02984431,0.0001217157,0.9687606,0.00006581287,0.00003287427,0.00003379238,0.00002804847,0.0004048159,0.0007080202],"genre_scores_gemma":[0.5055857,0.0002987053,0.4918576,0.00007183607,0.00005879007,0.0001226869,0.0002265823,0.00005892006,0.001719324],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0008321746,"threshold_uncertainty_score":0.00315994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02648435573738927,"score_gpt":0.2448028042011939,"score_spread":0.2183184484638047,"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."}}