{"id":"W4405936761","doi":"10.1109/icm63406.2024.10815775","title":"Machine Learning based Memory Load Value Predictor for Multimedia Applications","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Multimedia; Value (mathematics); Machine learning","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":[0.0001990077,0.0001174266,0.0001009022,0.0001147033,0.0001112687,0.0001113936,0.0008297308,0.00006312175,0.0000238016],"category_scores_gemma":[0.0002149503,0.00009914112,0.0000524527,0.0003820865,0.00006083069,0.0004381379,0.0002543927,0.0001851937,0.0001171289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000943712,"about_ca_system_score_gemma":0.0001165319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001308356,"about_ca_topic_score_gemma":0.000005375036,"domain_scores_codex":[0.9989859,0.00001367857,0.0001460956,0.0004542743,0.0001869961,0.000213011],"domain_scores_gemma":[0.9988437,0.0004268257,0.00002860376,0.0005992188,0.00005413193,0.00004750111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006625038,0.00007082166,0.00005226472,0.0001733296,0.00003542778,0.00001563273,0.0001945313,0.01150784,0.003372828,0.2420061,0.006496605,0.736068],"study_design_scores_gemma":[0.0001365531,0.00003681439,0.000008537752,0.00001090681,0.00000503764,0.000002363402,0.0000113856,0.8192683,0.003965893,0.006951885,0.1694976,0.0001046853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000211452,0.001061788,0.9915037,0.001278331,0.0001870947,0.0005077149,0.00004867486,0.004429148,0.0009623954],"genre_scores_gemma":[0.04879456,0.00001763989,0.9484188,0.0001735839,0.0000705184,0.0006502909,0.00004998844,0.00001825912,0.001806366],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8077605,"threshold_uncertainty_score":0.4042858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01475622945990219,"score_gpt":0.2683446567429991,"score_spread":0.2535884272830969,"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."}}