{"id":"W4408100835","doi":"10.1109/acai63924.2024.10899564","title":"Microarchitectural Analysis of Pre-Processing Stage in Machine Learning Workloads","year":2024,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Becton Dickinson (Canada)","funders":"","keywords":"Computer science; Stage (stratigraphy); 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":[0.0005042427,0.0009034726,0.0002921004,0.0008604705,0.00039781,0.0007053064,0.001142739,0.000301843,0.004177967],"category_scores_gemma":[0.002117768,0.0003783411,0.0003723621,0.0008412407,0.0003876272,0.001420111,0.0003430422,0.000734372,0.000755167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201419,"about_ca_system_score_gemma":0.00141898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003243508,"about_ca_topic_score_gemma":0.005598119,"domain_scores_codex":[0.9993562,0.00006629434,0.00003091833,0.0001267035,0.0002492527,0.0001706127],"domain_scores_gemma":[0.9983194,0.0006953083,0.0001798691,0.0002257601,0.0005051009,0.0000745151],"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":[0.001378275,0.0005358045,0.05092263,0.0009341201,0.0001767346,0.0009829937,0.0006363278,0.4104724,0.2921339,0.01404862,0.01816075,0.2096174],"study_design_scores_gemma":[0.00002264138,0.0006802103,0.01700229,0.00004371622,0.00008672065,0.0001571069,0.0001532739,0.8695769,0.1027532,0.003473428,0.006003709,0.000046759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.874823,0.002456298,0.1027197,0.0007062564,0.0001922496,0.0002147839,0.001393839,0.005194097,0.01229982],"genre_scores_gemma":[0.9691508,0.0003758016,0.02609424,0.000154428,0.00003406305,0.0001281289,0.0009661465,0.0002975445,0.002798774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004177967,"threshold_uncertainty_score":0.01397663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006385683205756124,"score_gpt":0.2252967446497851,"score_spread":0.2189110614440289,"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."}}