{"id":"W2169665194","doi":"10.1109/tencon.1991.753909","title":"Performance Evaluation Of Progressive Image Transmission Techniques","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Image (mathematics); Computer vision; Transmission (telecommunications); Artificial intelligence; Bandwidth (computing); Image restoration; Image compression; Image processing; Feature detection (computer vision); Computer graphics (images); Telecommunications","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":[0.000643422,0.0001065325,0.0001220956,0.000118245,0.00005519741,0.00002541693,0.0007317708,0.00004968898,0.0001401108],"category_scores_gemma":[0.00002520438,0.00008172757,0.00003515154,0.0002382531,0.00005024154,0.001768373,0.0001628457,0.00008310518,0.00001113825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004637964,"about_ca_system_score_gemma":0.00006709657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001457422,"about_ca_topic_score_gemma":1.897216e-7,"domain_scores_codex":[0.9986228,0.00007327107,0.000264584,0.0002689926,0.0006217605,0.0001486248],"domain_scores_gemma":[0.9988048,0.00002567006,0.0001380335,0.0005916844,0.0003915836,0.00004824789],"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":[0.000003327997,0.00004974125,0.00001998103,0.00000793443,0.000001613815,2.40603e-7,0.00006605069,0.00001522361,0.05024905,0.001274983,0.0008472326,0.9474646],"study_design_scores_gemma":[0.0001096127,0.00006438006,0.0002478007,0.00006519405,0.00000409786,0.000005088349,0.000002694537,0.2234628,0.7687241,0.0009207664,0.006304231,0.00008922214],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009612666,0.0001786066,0.9754627,0.0003933867,0.0000171569,0.0004649277,0.00000125317,0.0006910348,0.01317825],"genre_scores_gemma":[0.3627741,0.00003785028,0.6370049,0.00004543869,0.00001852115,0.0000643305,0.000002559382,0.000004646518,0.00004761858],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9473754,"threshold_uncertainty_score":0.3332753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123114707168851,"score_gpt":0.32884360806775,"score_spread":0.3076124609960615,"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."}}