{"id":"W4392114198","doi":"10.1109/lca.2024.3365149","title":"Improving Energy-Efficiency of Capsule Networks on Modern GPUs","year":2024,"lang":"en","type":"article","venue":"IEEE Computer Architecture Letters","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Computer architecture; Efficient energy use; Parallel computing; Energy (signal processing); Embedded system; Electrical engineering; Engineering","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":[0.0001824139,0.0002768163,0.0002539104,0.0003311426,0.0001030721,0.000260121,0.001054145,0.00007392275,0.000001567244],"category_scores_gemma":[0.000003722936,0.000233911,0.0002418537,0.0004054368,0.00006895306,0.0001466533,0.0002065234,0.0004519762,0.000008301633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004968937,"about_ca_system_score_gemma":0.0000382305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001173575,"about_ca_topic_score_gemma":0.0000055868,"domain_scores_codex":[0.9980735,0.0001062334,0.0002990101,0.0007028904,0.0003751115,0.0004433151],"domain_scores_gemma":[0.9989295,0.0001704208,0.00007106673,0.0006999816,0.00002842481,0.0001005997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007563319,0.00004099182,0.000004667814,0.00004256559,0.00004567863,0.0001575674,0.0006791466,0.4988951,0.04622314,0.00178382,0.003374927,0.4487448],"study_design_scores_gemma":[0.0001606734,0.0001354931,0.00002505921,0.0001502685,0.00001052238,0.00006756703,7.672759e-7,0.9948534,0.003309416,0.0004451038,0.0005787236,0.0002630291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07290875,0.0004651901,0.9205872,0.002183369,0.003230074,0.00008494854,0.00000319719,0.0004389154,0.00009834118],"genre_scores_gemma":[0.984622,0.000005009849,0.008207035,0.00628909,0.0007966595,0.000008338311,0.000002750016,0.00002613889,0.0000429659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9123802,"threshold_uncertainty_score":0.9538612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006455408577077102,"score_gpt":0.1883589122110158,"score_spread":0.1819035036339387,"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."}}