{"id":"W2135962321","doi":"10.1109/ccece.1993.332258","title":"Object-oriented image sequence coding using the minimum description length principle","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Minimum description length; Coding (social sciences); Computer science; Segmentation; Artificial intelligence; Computer vision; Motion estimation; Object (grammar); Image segmentation; Algorithm; Mathematics; 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":[0.0006590862,0.0004169911,0.0004449225,0.0009153661,0.0001784312,0.0007415228,0.0008043947,0.0005263966,0.001729596],"category_scores_gemma":[0.001504972,0.0001794337,0.0003302037,0.001010998,0.000527878,0.001090744,0.0005987963,0.0006922243,0.0008390377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006130411,"about_ca_system_score_gemma":0.0006612454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001336001,"about_ca_topic_score_gemma":0.001151662,"domain_scores_codex":[0.9995444,0.00009586725,0.00002803645,0.00003220971,0.0002709746,0.00002843614],"domain_scores_gemma":[0.9996006,0.0001355103,0.00004346879,0.00007854195,0.0001283534,0.000013493],"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":[0.0001730147,0.00005026902,0.0002688074,0.0002602994,0.00003056473,0.0001974076,0.0002116671,0.1144927,0.06305049,0.361489,0.006386736,0.453389],"study_design_scores_gemma":[0.00004221602,0.00009471621,0.0002507769,0.00006037283,0.00001417774,0.000201266,0.00002250789,0.8638795,0.03766546,0.07774764,0.01998171,0.00003964486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00192836,0.0002837703,0.996008,0.00008610002,0.00002300133,0.00003623012,0.00004848413,0.0002386491,0.001347449],"genre_scores_gemma":[0.08649324,0.0009469586,0.9066929,0.0001369753,0.00008581258,0.0002464656,0.0005030743,0.0001090194,0.004785664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001729596,"threshold_uncertainty_score":0.005786121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0837899809299924,"score_gpt":0.3204365285823454,"score_spread":0.236646547652353,"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."}}