{"id":"W4412624670","doi":"10.1109/apsit63993.2025.11086109","title":"Maximizing SER Performance with ICR-SEA: A Novel Framework for Grid-Search Optimization","year":2025,"lang":"en","type":"article","venue":"","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Grid; Distributed computing; Mathematical optimization; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002007491,0.001970426,0.001460151,0.0007803501,0.0003723698,0.001066403,0.001921623,0.001369566,0.002686526],"category_scores_gemma":[0.005401454,0.0006317373,0.0008459662,0.0005944434,0.0009157812,0.001277193,0.001586886,0.001504524,0.0009424274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000784589,"about_ca_system_score_gemma":0.001399811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004515499,"about_ca_topic_score_gemma":0.005982774,"domain_scores_codex":[0.9993502,0.0002721105,0.00003913015,0.000151084,0.0001123215,0.00007513636],"domain_scores_gemma":[0.9989772,0.0005626485,0.00008430886,0.0001467012,0.0001815067,0.0000477088],"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":[0.0000814982,0.00006441697,0.0006920621,0.00006531418,0.00005707022,0.00005923542,0.0000471571,0.9469532,0.001261428,0.005680256,0.002136298,0.04290203],"study_design_scores_gemma":[0.000005107048,0.00001933265,0.00002779201,0.000003685502,0.000002936039,0.000005637707,0.000004517285,0.9979411,0.0001996562,0.001578356,0.0002098088,0.000002185613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01943546,0.0004542487,0.9738562,0.0003087585,0.00006430868,0.0000911961,0.00008472133,0.001797425,0.003907647],"genre_scores_gemma":[0.5787967,0.0003048624,0.414451,0.0005682351,0.0001027614,0.0004115078,0.0004926146,0.0007773514,0.004094974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004515499,"threshold_uncertainty_score":0.01061672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176823255557007,"score_gpt":0.2669034494440033,"score_spread":0.2451352168884332,"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."}}