{"id":"W1967734985","doi":"10.1109/tip.2012.2202672","title":"$\\ell_{2}$ Restoration of $\\ell_{\\infty}$-Decoded Images Via Soft-Decision Estimation","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Decoding methods; Notation; Coding (social sciences); Algorithm; Mathematics; Computer science; Discrete mathematics; Artificial intelligence; Statistics; Arithmetic","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002022276,0.0002453544,0.0002454368,0.0003025822,0.0001944927,0.00008349323,0.0001367973,0.000134336,0.00004628067],"category_scores_gemma":[0.00001307856,0.0002537714,0.00009469167,0.0003606583,0.00007803305,0.001316871,0.000001801777,0.0002681389,0.00004403907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009251491,"about_ca_system_score_gemma":0.00002470268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001526808,"about_ca_topic_score_gemma":0.000003428072,"domain_scores_codex":[0.9987424,0.00002838532,0.0004270209,0.000195982,0.0002899673,0.000316269],"domain_scores_gemma":[0.9992353,0.00008984406,0.0001149225,0.0003012227,0.000165979,0.00009278445],"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":[0.00003679765,0.000116539,0.000008364838,0.00009614741,0.00001937746,0.000001481048,0.0003796045,0.07118715,0.4414124,0.000002841324,0.0003902022,0.4863491],"study_design_scores_gemma":[0.0001850786,0.00003613643,0.00007412533,0.0002156637,0.00004694048,0.00001508187,0.00003337476,0.283145,0.7155252,0.0004310152,0.00008438977,0.000208043],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03402837,0.0004428622,0.963267,0.00002048353,0.0004212878,0.0001930219,0.000008010868,0.0008293476,0.0007895952],"genre_scores_gemma":[0.8938748,0.00005132078,0.1058552,0.00002284298,0.00006803466,0.00002444634,0.000004816664,0.00005976651,0.0000388077],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8598464,"threshold_uncertainty_score":0.9999915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01466321925222321,"score_gpt":0.259912541784106,"score_spread":0.2452493225318828,"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."}}