{"id":"W1712101933","doi":"10.1109/dcc.1994.305936","title":"Fast bintree-structured image coder for high subjective quality","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Image compression; Coding (social sciences); Texture compression; Image (mathematics); Artificial intelligence; Image texture; Encoding (memory); Piecewise; Data compression; Texture (cosmology); Block (permutation group theory); Image quality; Segmentation; Variable (mathematics); Image segmentation; Computer vision; Pattern recognition (psychology); Algorithm; Mathematics; Image processing; Statistics; Combinatorics","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":[0.0005768324,0.0004177964,0.0003737666,0.0008099778,0.0002690107,0.0006861966,0.0006355845,0.0005556758,0.009419261],"category_scores_gemma":[0.001782237,0.0001796615,0.0001626224,0.000820932,0.000297723,0.0008103715,0.0004493268,0.0007201559,0.002606815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003952101,"about_ca_system_score_gemma":0.000478461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001161039,"about_ca_topic_score_gemma":0.002262912,"domain_scores_codex":[0.9994704,0.00007002111,0.00002039844,0.00003428569,0.0003792015,0.0000256463],"domain_scores_gemma":[0.9987996,0.0002965258,0.0000758465,0.0001795877,0.0005985029,0.0000498903],"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":[0.0005160522,0.00006959813,0.0004528994,0.0002618193,0.00002676342,0.0002087176,0.0001447253,0.008171353,0.3661227,0.01727967,0.01190664,0.5948391],"study_design_scores_gemma":[0.0001961966,0.0005748916,0.002224995,0.0001148644,0.00006039717,0.001874554,0.00007507524,0.4355263,0.4846293,0.005683465,0.06892311,0.0001168554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01267764,0.0003878735,0.9806985,0.00016349,0.00007443703,0.0001198294,0.0001763642,0.002678018,0.003023773],"genre_scores_gemma":[0.1210093,0.0004514936,0.865727,0.000222489,0.00007198267,0.0002027912,0.0006076038,0.0006181538,0.01108922],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009419261,"threshold_uncertainty_score":0.03151059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028425744165599,"score_gpt":0.3066374682132667,"score_spread":0.2782117240476677,"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."}}