{"id":"W129115577","doi":"10.1007/978-1-4615-1527-2_9","title":"Parallel Processing for Image Restoration","year":2001,"lang":"en","type":"book-chapter","venue":"The Kluwer international series on Asian studies in computer and information science","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Block (permutation group theory); Jump; Image (mathematics); Computation; Matching (statistics); Algorithm; Image restoration; Blossom algorithm; Coding (social sciences); Transmission (telecommunications); Image processing; Artificial intelligence; Mathematics","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":[0.0007124331,0.0003140995,0.0002826065,0.0006164009,0.00056298,0.0007851402,0.001858933,0.00009033527,0.000006259585],"category_scores_gemma":[0.00006619808,0.0002368276,0.00005745216,0.0002281017,0.0008876537,0.0114564,0.001165383,0.0002798458,0.00002028055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002692014,"about_ca_system_score_gemma":0.0001233256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001615741,"about_ca_topic_score_gemma":0.000008441393,"domain_scores_codex":[0.9977024,0.0000153314,0.000685991,0.0004734508,0.0008535146,0.0002692908],"domain_scores_gemma":[0.9978174,0.0001225411,0.0005373767,0.0005410085,0.0009189612,0.00006270315],"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":[0.00005189945,0.00001326866,0.000003469251,0.00004925622,0.00002012972,0.000004528843,0.002101705,0.0002356776,0.000005336719,0.6083188,0.008298685,0.3808973],"study_design_scores_gemma":[0.0004389487,0.0002348907,0.0001213242,0.0004825079,0.000005429175,0.00008887172,0.0002015485,0.05235308,0.0000499609,0.08629897,0.8592469,0.0004775602],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000003131222,0.0001233085,0.8650518,0.002506208,0.001163706,0.0005512164,0.00002978688,0.0001508368,0.13042],"genre_scores_gemma":[0.01243995,0.004168307,0.9494011,0.008923235,0.001134384,0.0005960236,0.0001884256,0.00006007468,0.02308855],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8509482,"threshold_uncertainty_score":0.965755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03706614385815926,"score_gpt":0.3332019958444584,"score_spread":0.2961358519862991,"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."}}