{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002803785,0.0005394585,0.000427848,0.0005929637,0.000234074,0.0005675125,0.0006031894,0.0003785006,0.001351134],"category_scores_gemma":[0.00143835,0.0001490512,0.0001619808,0.0006130729,0.0002184719,0.0008695604,0.0003230534,0.0005387404,0.0004074342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005499319,"about_ca_system_score_gemma":0.0005223334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003991791,"about_ca_topic_score_gemma":0.004158704,"domain_scores_codex":[0.9998699,0.0000204509,0.000008874466,0.00002791534,0.00005343492,0.00001946527],"domain_scores_gemma":[0.9995871,0.000159391,0.00005825737,0.00003743443,0.0001431427,0.0000146531],"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":[0.0004208027,0.0002125499,0.005973917,0.00009816587,0.00004064749,0.0001243954,0.00006495995,0.5806372,0.02457519,0.002712511,0.003044172,0.3820955],"study_design_scores_gemma":[0.000001230317,0.00001534493,0.0002651945,0.000001881422,0.000001857934,0.000006239495,0.000003450068,0.9973422,0.001903297,0.0002897664,0.0001672234,0.000002241776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3323485,0.001842397,0.657333,0.0004796881,0.0001291089,0.0000728501,0.0002478873,0.004266945,0.003279571],"genre_scores_gemma":[0.9495162,0.0003222995,0.04765869,0.00005930688,0.0000387004,0.00005071862,0.000167521,0.0000475519,0.002138928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003991791,"threshold_uncertainty_score":0.007937074,"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."}}