{"id":"W4414053381","doi":"10.2139/ssrn.5458055","title":"Pairs of Compactly Supported Gabor Dual Frames with High smoothness and Small Condition Numbers","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Dual (grammatical number); Gabor wavelet; Smoothness; Window (computing); Gabor transform; Smoothing; Parametric statistics; Translation (biology)","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":[0.0007704029,0.001049392,0.0009788903,0.002675789,0.0006595191,0.003281412,0.000833515,0.002063189,0.007748949],"category_scores_gemma":[0.003916691,0.0006781856,0.0007093466,0.0008881861,0.001510644,0.002374671,0.00239168,0.002473552,0.001546595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005412388,"about_ca_system_score_gemma":0.0003611646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000216969,"about_ca_topic_score_gemma":0.000220987,"domain_scores_codex":[0.9993774,0.0001283018,0.00003408248,0.0001684622,0.0001953311,0.00009633013],"domain_scores_gemma":[0.9986223,0.0002774278,0.0002520398,0.0002180862,0.0003628286,0.0002673527],"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":[0.0009668312,0.0001980769,0.001405947,0.0001958518,0.00007050468,0.0007573364,0.0002668949,0.004092792,0.05188273,0.8814542,0.003413773,0.05529518],"study_design_scores_gemma":[0.000209248,0.000547129,0.003977267,0.0001116117,0.000114268,0.002834201,0.000634159,0.1707225,0.03458517,0.7711627,0.01494338,0.0001584137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2610437,0.000794462,0.7105075,0.0007606935,0.000874951,0.0001089127,0.0004493419,0.0003164936,0.02514389],"genre_scores_gemma":[0.8418636,0.0005999673,0.132205,0.0004008261,0.0004264508,0.0001482603,0.000793384,0.0003469372,0.02321549],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007748949,"threshold_uncertainty_score":0.02592283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167752227097048,"score_gpt":0.2653966856300164,"score_spread":0.253719163359046,"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."}}