{"id":"W2136625298","doi":"10.1142/s0219691314500039","title":"RAMANUJAN SUMS FOR IMAGE PATTERN ANALYSIS","year":2013,"lang":"en","type":"article","venue":"International Journal of Wavelets Multiresolution and Information Processing","topic":"Fractal and DNA sequence analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Concordia University","funders":"","keywords":"Invariant (physics); Pattern recognition (psychology); Complex wavelet transform; Mathematics; Ramanujan's sum; Artificial intelligence; Zernike polynomials; Wavelet; Algorithm; Translation (biology); Scaling; Image processing; White noise; Rotation (mathematics); Image (mathematics); Computer science; Wavelet transform; Combinatorics; Geometry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00153062,0.001290878,0.00134277,0.003388587,0.0006133859,0.002392356,0.001524812,0.001321321,0.0100511],"category_scores_gemma":[0.004818605,0.0004384324,0.001263131,0.004226421,0.001645752,0.002164726,0.002098671,0.003203063,0.007774291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009228851,"about_ca_system_score_gemma":0.0007833716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001037888,"about_ca_topic_score_gemma":0.0008464186,"domain_scores_codex":[0.9987072,0.000405501,0.00009367152,0.0002071233,0.0005214945,0.0000650689],"domain_scores_gemma":[0.9987249,0.0006033495,0.00009360593,0.0002905131,0.0002368674,0.00005070818],"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":[0.00005058923,0.00004454689,0.0003447694,0.0005710094,0.00009492206,0.0001914834,0.0002060071,0.02833295,0.006280416,0.6257151,0.01691867,0.3212495],"study_design_scores_gemma":[0.00001234358,0.00003340174,0.0004346629,0.0001420107,0.00002528129,0.0002939035,0.00005653091,0.1779917,0.002046823,0.7365649,0.08234363,0.00005475908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002956794,0.02103304,0.9527553,0.0009731929,0.0008189786,0.0001072657,0.0003869695,0.0009077075,0.02006077],"genre_scores_gemma":[0.1369195,0.02716725,0.8018565,0.0006309645,0.002746444,0.0007448183,0.001238359,0.0006421549,0.02805401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0100511,"threshold_uncertainty_score":0.03362429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006071852911256522,"score_gpt":0.2587789379201519,"score_spread":0.2527070850088954,"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."}}