{"id":"W85012173","doi":"","title":"Benefits of hybrid DCT domain image matching","year":2000,"lang":"en","type":"article","venue":"Queensland's institutional digital repository (The University of Queensland)","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Discrete cosine transform; Pixel; Algorithm; Mathematics; Matching (statistics); Resampling; Image (mathematics); Window (computing); Image quality; Computer science; Artificial intelligence; Statistics","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":[0.0006897768,0.0004830367,0.0005062034,0.0007646501,0.0002670758,0.000782709,0.0008942351,0.0008038434,0.003895544],"category_scores_gemma":[0.003314151,0.0003025554,0.000412988,0.00122967,0.0002500282,0.00129855,0.001110419,0.000462572,0.001854356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002053722,"about_ca_system_score_gemma":0.0003569227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001127415,"about_ca_topic_score_gemma":0.00137103,"domain_scores_codex":[0.9991228,0.0001436407,0.00004537074,0.000119458,0.0005173781,0.00005134417],"domain_scores_gemma":[0.9987716,0.0003375798,0.00006883801,0.000383326,0.0004072596,0.00003129828],"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":[0.0006883801,0.0002451161,0.002476237,0.000162259,0.0000741352,0.0002727543,0.00008285607,0.04483076,0.1661128,0.01587714,0.004056788,0.7651208],"study_design_scores_gemma":[0.0001276304,0.0005639527,0.004971581,0.00004620153,0.000103376,0.003630513,0.000101052,0.7850915,0.159182,0.01139211,0.03471135,0.00007881009],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04506849,0.0006598953,0.9404191,0.00030798,0.0001317043,0.00008510306,0.0001296255,0.001477046,0.01172112],"genre_scores_gemma":[0.3465829,0.0005347676,0.6382146,0.0003409777,0.0001459951,0.00006924028,0.000441933,0.0002523104,0.01341722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003895544,"threshold_uncertainty_score":0.0130319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007431639703100855,"score_gpt":0.2001377694708742,"score_spread":0.1927061297677734,"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."}}