{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001349741,0.0002142512,0.0003053614,0.0001248681,0.0004725215,0.0000825574,0.001411307,0.00006121199,0.00005091988],"category_scores_gemma":[0.00002173475,0.0001831856,0.0001853555,0.0002372007,0.0006287257,0.001861679,0.0003767907,0.0002106575,0.00004666665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007640536,"about_ca_system_score_gemma":0.0001711416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001961169,"about_ca_topic_score_gemma":0.000005817653,"domain_scores_codex":[0.9983599,0.0000755199,0.0003487654,0.0004153512,0.0005513255,0.0002491363],"domain_scores_gemma":[0.9985202,0.0001639118,0.0002487802,0.000769927,0.0001884336,0.0001087508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001683745,0.001966877,0.01299537,0.0004792544,0.0007241581,0.001749265,0.005426169,0.03567619,0.01647489,0.6451842,0.03158079,0.2460591],"study_design_scores_gemma":[0.008306187,0.001571088,0.1762081,0.003328349,0.0002299479,0.005232765,0.001167773,0.008587312,0.1456535,0.2267016,0.4188478,0.004165587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5107125,0.0001902856,0.4192268,0.0002797629,0.0001723593,0.0002907755,0.0002408748,0.0002726664,0.06861395],"genre_scores_gemma":[0.9673883,0.00006570244,0.03115011,0.00004185666,0.00005327834,7.740592e-7,0.00004524013,0.00000941192,0.001245283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4566759,"threshold_uncertainty_score":0.7470093,"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."}}