{"id":"W4387701050","doi":"10.1145/3617946.3617951","title":"Towards a Research Agenda for Understanding and Managing Uncertainty in Self-Adaptive Systems","year":2023,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; York University","funders":"Christian Doppler Forschungsgesellschaft; Bundesministerium für Digitalisierung und Wirtschaftsstandort; Österreichische Nationalstiftung für Forschung, Technologie und Entwicklung","keywords":"Computer science; Agile software development; Human systems engineering; Uncertainty analysis; Risk analysis (engineering); Adaptive system; Complex adaptive system; Key (lock); Management science; Engineering; Artificial intelligence; Simulation; Computer security; Software engineering; Business","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002889653,0.0003319065,0.0004264334,0.00106519,0.0002164736,0.0002320756,0.001123707,0.0001664783,4.928376e-7],"category_scores_gemma":[0.1218971,0.0003535665,0.00007183071,0.002033738,0.00005378926,0.0005413959,0.0009964164,0.0004912664,0.000007121104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006010673,"about_ca_system_score_gemma":0.00009462618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007510868,"about_ca_topic_score_gemma":0.00000623735,"domain_scores_codex":[0.9972051,0.000133209,0.0003747439,0.0007769403,0.0004586565,0.001051345],"domain_scores_gemma":[0.8858163,0.112983,0.00006449554,0.0008584839,0.0001368127,0.000140864],"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":[0.0000245772,0.00002487034,0.00420378,0.0009295018,0.0000844047,0.000143283,0.004164731,0.9134496,0.0003677585,0.06496937,0.0003194424,0.01131864],"study_design_scores_gemma":[0.002689491,0.0007783048,0.03543788,0.002017887,0.00004114047,0.0001106737,0.002308191,0.8545064,0.001089594,0.09573766,0.002395525,0.002887226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01105998,0.0007755092,0.9826792,0.0002885362,0.0008328602,0.0006226325,0.00001400413,0.003724755,0.000002557081],"genre_scores_gemma":[0.5203241,0.0001035449,0.4791681,0.00001360248,0.00007473628,0.0002389975,0.000006313111,0.00005559189,0.0000150306],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5092641,"threshold_uncertainty_score":0.9998916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2246854830976646,"score_gpt":0.3680591670854527,"score_spread":0.1433736839877881,"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."}}