{"id":"W4378676681","doi":"10.1109/icstw58534.2023.00069","title":"Test Cost Reduction for 5G and Beyond using Machine Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); University of Ottawa; Carleton University","funders":"","keywords":"Reduction (mathematics); Test (biology); Computer science; Cost reduction; Machine learning; Artificial intelligence; Mathematics; Geology","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":[0.0003146495,0.00006320507,0.00006754897,0.0001050013,0.0002031385,0.0001051249,0.0001258987,0.00002894275,0.000001326651],"category_scores_gemma":[0.0005202555,0.00005773437,0.00001531935,0.0003208535,0.00002031745,0.0001574479,0.00006515229,0.00006456894,0.000004457442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001513901,"about_ca_system_score_gemma":0.00001508647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009878925,"about_ca_topic_score_gemma":0.000001729829,"domain_scores_codex":[0.9994742,0.00001303109,0.0000848148,0.0002073771,0.0000718307,0.00014878],"domain_scores_gemma":[0.9993896,0.0003601795,0.00003377515,0.0001390797,0.00004210575,0.00003528763],"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":[0.00001541269,0.0001209601,0.1056545,0.0001849399,0.00003125912,0.00002477277,0.002174866,0.002237126,0.03585198,0.01596124,0.07201507,0.7657279],"study_design_scores_gemma":[0.0001234739,0.00009351574,0.0006508058,0.00001958068,0.000003216768,0.00006722941,0.000007277887,0.9707329,0.004569714,0.02229056,0.001322194,0.0001195621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02894617,0.00006651194,0.9452655,0.0009135034,0.000234967,0.0002711916,0.00000178282,0.02349451,0.0008058206],"genre_scores_gemma":[0.5043177,0.00001061574,0.4947465,0.00008977175,0.00006404348,0.00002070141,0.000005436877,0.00001168663,0.0007335403],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9684957,"threshold_uncertainty_score":0.2354339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04976053073262066,"score_gpt":0.3063258694206697,"score_spread":0.2565653386880491,"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."}}