{"id":"W2147370385","doi":"10.1109/ccece.2005.1557129","title":"Implementation of three SIMD algorithms for graphical user interface processing in mobile devices using the Atsana J2210 media processor","year":2006,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"SIMD; Computer science; Reduced instruction set computing; Rendering (computer graphics); Mobile device; Algorithm; Parallel computing; Computer hardware; Instruction set; Computer graphics (images); Operating system","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":[0.0002388986,0.0006005252,0.0002463808,0.0003893893,0.000294814,0.0006674964,0.0008572931,0.0002616844,0.00521274],"category_scores_gemma":[0.0009365978,0.0002243704,0.0003308721,0.0003832311,0.0002670035,0.0004850864,0.000360225,0.0004404839,0.001069065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006034666,"about_ca_system_score_gemma":0.000664359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001606522,"about_ca_topic_score_gemma":0.001927004,"domain_scores_codex":[0.9998038,0.00002510582,0.00001392589,0.0000306489,0.0001011347,0.0000253111],"domain_scores_gemma":[0.9997037,0.00008874917,0.00002790234,0.00006384558,0.00009440409,0.00002136953],"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":[0.001602406,0.0003394425,0.004647713,0.0003328869,0.0001264275,0.0004419984,0.000432418,0.1569653,0.1826811,0.03393282,0.01215424,0.6063433],"study_design_scores_gemma":[0.0002907207,0.0005707827,0.001387077,0.00002730622,0.00005650307,0.0003089507,0.00009656294,0.7528856,0.2028168,0.004643294,0.03685982,0.00005666463],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09353435,0.0001520224,0.88309,0.000187299,0.00008443282,0.0002055765,0.0001910844,0.005652754,0.01690249],"genre_scores_gemma":[0.38308,0.0001437473,0.6096392,0.0001599941,0.00002795359,0.00025765,0.000461597,0.0004316918,0.005798107],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00521274,"threshold_uncertainty_score":0.01743841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03224298130848954,"score_gpt":0.342869479254539,"score_spread":0.3106264979460495,"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."}}