{"id":"W2030877982","doi":"10.1109/iscas.2010.5537457","title":"Comparison of Haar wavelet-based and Poisson-based numerical integration techniques","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Haar wavelet; Wavelet; Poisson distribution; Computation; Haar; Computer science; Convergence (economics); Decomposition; Algorithm; Image (mathematics); Wavelet transform; Wavelet packet decomposition; Mathematics; Mathematical optimization; Applied mathematics; Computer vision; Artificial intelligence; Discrete wavelet transform; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002198138,0.000137602,0.0002198147,0.0001413949,0.00006750354,0.00008306908,0.0004728292,0.00009041135,0.00001131665],"category_scores_gemma":[0.0001573329,0.0001138901,0.00003390271,0.0002818718,0.0001398163,0.0003748939,0.00008234259,0.0002645025,0.000001587115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001569958,"about_ca_system_score_gemma":0.00008322808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000311527,"about_ca_topic_score_gemma":0.000009822439,"domain_scores_codex":[0.9990308,0.00003046471,0.0002735896,0.000303044,0.0002050337,0.0001570378],"domain_scores_gemma":[0.9990274,0.0001256033,0.0001554885,0.0004408202,0.0001869832,0.00006373921],"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":[0.00001193589,0.0001965197,0.001822992,0.00003187121,0.000002134686,0.000001413243,0.00008951453,0.000001414479,0.4716167,0.0248814,0.0005554599,0.5007886],"study_design_scores_gemma":[0.00006532761,0.00009701773,0.0002685705,0.00001947892,0.00000166567,0.000001188267,0.000003911367,0.3772885,0.6187143,0.003030153,0.0004162368,0.0000935657],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002145954,0.00002310338,0.9947543,0.001189189,0.00004222686,0.0001440425,8.315847e-7,0.0009185568,0.0007817985],"genre_scores_gemma":[0.4860371,2.827382e-7,0.5137452,0.0001821804,0.000007112093,0.0000121583,0.000001488406,0.000005286783,0.000009175585],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5006951,"threshold_uncertainty_score":0.4644304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01628314003304467,"score_gpt":0.3361222118472482,"score_spread":0.3198390718142036,"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."}}