{"id":"W4384158036","doi":"10.1109/netsoft57336.2023.10175410","title":"AppleSeed: Intent-Based Multi-Domain Infrastructure Management via Few-Shot Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Pipeline (software); Executable; Compiler; Domain (mathematical analysis); Plan (archaeology); Software deployment; Software engineering; Artificial intelligence; Programming language","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005969746,0.0001895516,0.0001903508,0.0002270166,0.0002295878,0.0001444055,0.0007508096,0.00009073842,0.0000761197],"category_scores_gemma":[0.00002166143,0.0001438083,0.0001035015,0.001043985,0.00004876346,0.0002442831,0.0004493101,0.0002338153,0.0008700097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008120222,"about_ca_system_score_gemma":0.00003048139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003301589,"about_ca_topic_score_gemma":0.000007330815,"domain_scores_codex":[0.9983146,0.00007957583,0.0002912638,0.0005006111,0.0003809387,0.0004330101],"domain_scores_gemma":[0.9991448,0.00006509534,0.00007339877,0.0005448101,0.00006597288,0.0001059044],"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":[0.00006495332,0.0003292228,0.3992791,0.001571958,0.0002847243,0.0002934532,0.003835497,0.09140052,0.002593629,0.0161069,0.02305448,0.4611855],"study_design_scores_gemma":[0.001496565,0.0001167058,0.122067,0.00008272059,0.00000955934,0.0000120158,0.0009177504,0.8416789,0.0007844844,0.001501799,0.03079209,0.0005404461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06123828,0.00001262479,0.9338518,0.0007191449,0.0006537591,0.0003687247,7.317106e-7,0.001467225,0.001687759],"genre_scores_gemma":[0.924554,0.000007177267,0.07293518,0.000356093,0.00004895095,0.00006766772,0.00001494188,0.00001511597,0.002000903],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8633157,"threshold_uncertainty_score":0.9999079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506456338430544,"score_gpt":0.2519379432568455,"score_spread":0.2368733798725401,"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."}}