{"id":"W4415104121","doi":"10.1109/icst66402.2025.11512369","title":"Sparse Signal Blind Deconvolution using Bayesian MAP Estimation","year":2025,"lang":"","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"Safran","keywords":"Deconvolution; Pattern recognition (psychology); Blind deconvolution; Bayesian probability; SIGNAL (programming language); Noise (video); Signal processing; Bayes estimator","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":[0.001168449,0.0003504651,0.0003304397,0.000781464,0.0004687283,0.0009852289,0.0007946322,0.0003469066,0.0004647599],"category_scores_gemma":[0.00005890402,0.0003929186,0.0001580503,0.001354262,0.000147175,0.00183366,0.0003950388,0.0003639309,0.0001479236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003345569,"about_ca_system_score_gemma":0.0009307171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001774544,"about_ca_topic_score_gemma":0.00005571156,"domain_scores_codex":[0.9970221,0.0003710932,0.0008641361,0.0008153382,0.0004429553,0.0004843552],"domain_scores_gemma":[0.9982871,0.0001330458,0.0003037421,0.0007958404,0.0003354608,0.0001447831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009306285,0.0004783793,0.0005619161,0.0001689887,0.0001134987,0.0000121001,0.001742254,0.05028153,0.003263144,0.6926583,0.007230141,0.2433967],"study_design_scores_gemma":[0.0005766865,0.00008528789,0.0002580358,0.0002041798,0.00004661407,0.000008203556,0.00004341989,0.941524,0.01987617,0.0356654,0.001374702,0.0003373206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004044867,0.0002633702,0.9807364,0.003302758,0.0007811771,0.0007202656,0.000002370668,0.0005160176,0.009632809],"genre_scores_gemma":[0.6063099,0.00001109803,0.3900837,0.001184785,0.00005007378,0.00001216003,0.00000611964,0.00001079747,0.00233137],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8912424,"threshold_uncertainty_score":0.9998523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03323537973859565,"score_gpt":0.318725291193863,"score_spread":0.2854899114552674,"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."}}