{"id":"W4410211991","doi":"10.3390/e27050506","title":"Karatsuba Algorithm Revisited for 2D Convolution Computation Optimization","year":2025,"lang":"en","type":"article","venue":"Entropy","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multiplication (music); Convolution (computer science); Computer science; Matrix multiplication; Operand; Computation; Reduction (mathematics); Algorithm; Parallel computing; Arithmetic; Mathematics; Artificial intelligence","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":[0.0004122142,0.000623596,0.0005021184,0.0005508389,0.0004802832,0.0009762936,0.0006868305,0.000552594,0.005221443],"category_scores_gemma":[0.001196926,0.0002938364,0.0006134897,0.0008476457,0.0005438275,0.0009707207,0.0007038742,0.0007898174,0.001092728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006463247,"about_ca_system_score_gemma":0.001099186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002095064,"about_ca_topic_score_gemma":0.002921394,"domain_scores_codex":[0.9996582,0.00007374616,0.00001948409,0.00005619919,0.0001548888,0.0000374165],"domain_scores_gemma":[0.9997414,0.0001321673,0.00002172938,0.00003105885,0.00006346372,0.00001022388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001591514,0.00006284287,0.0007874797,0.0003381409,0.00007310383,0.0001995102,0.0002469395,0.582449,0.026998,0.1232154,0.003306323,0.2621641],"study_design_scores_gemma":[0.00002450187,0.00006603108,0.0001655158,0.00002821517,0.0000159443,0.0001162502,0.0000294379,0.9545709,0.007597619,0.02660042,0.01076935,0.00001579218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004942555,0.0003415466,0.9900928,0.00007919555,0.00002875394,0.0000216711,0.00001651259,0.0002427559,0.004234224],"genre_scores_gemma":[0.2574272,0.0008384267,0.7332159,0.0001271617,0.00005412636,0.0001856887,0.0001157457,0.0002387725,0.007797055],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005221443,"threshold_uncertainty_score":0.0174675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01295184550081136,"score_gpt":0.3030099169044709,"score_spread":0.2900580714036596,"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."}}