{"id":"W2363084458","doi":"","title":"Low Contrast Target Recognition in Cluttered Background with Optical Correlation","year":2013,"lang":"en","type":"article","venue":"Bandaoti guangdian","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Artificial intelligence; Contrast (vision); Computer vision; Computer science; Pattern recognition (psychology); Wavelet transform; Joint (building); Correlation; Wavelet; Mathematics; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007042501,0.000130966,0.00014577,0.0001439751,0.00003539634,0.00008508136,0.000056974,0.0001211768,0.0008929168],"category_scores_gemma":[0.00002507498,0.0001201203,0.00002460033,0.0002971057,0.00003953231,0.0003561798,0.000006937363,0.0001944349,0.001490067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006638373,"about_ca_system_score_gemma":0.00001481936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004110494,"about_ca_topic_score_gemma":0.00008271768,"domain_scores_codex":[0.9992367,0.00001794683,0.0002054494,0.0001440097,0.0001262847,0.0002696242],"domain_scores_gemma":[0.9996404,0.00005095876,0.00001693427,0.0001110621,0.00004628537,0.0001343274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005539165,0.002227354,0.3142923,0.001468878,0.0005654219,0.0002564825,0.003939937,0.1956378,0.04382737,0.01165436,0.03952688,0.3860493],"study_design_scores_gemma":[0.005354201,0.0003355604,0.5534533,0.0003505988,0.00004294064,0.00003973939,0.0005561998,0.4244826,0.008853592,0.002477013,0.002737242,0.001317045],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9168759,0.00005438155,0.06305011,0.0003092623,0.0003200085,0.0004106003,0.00001613385,0.000235447,0.01872813],"genre_scores_gemma":[0.995223,0.000008128585,0.004220396,0.0001641229,0.00008486653,0.00002485002,0.0001134419,0.0000316923,0.0001295306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3847323,"threshold_uncertainty_score":0.9992874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011554385651824,"score_gpt":0.1906221646441962,"score_spread":0.1805066207876779,"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."}}