{"id":"W2168328460","doi":"10.5555/2075144.2075179","title":"System identification for adaptive software systems: a requirements engineering perspective","year":2011,"lang":"en","type":"article","venue":"International Conference on Conceptual Modeling","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Identification (biology); Computer science; Process (computing); Perspective (graphical); Control engineering; Control system; Requirements engineering; System identification; Adaptive control; Software system; Adaptive system; Software; Control (management); Control theory (sociology); Engineering; Data modeling; Software engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004084506,0.0002233154,0.0002193921,0.0002022459,0.00008927452,0.0001287476,0.001051958,0.00008654629,0.000004714935],"category_scores_gemma":[0.0007982713,0.0002334498,0.00008118528,0.0001179415,0.00003829565,0.0007551654,0.000141722,0.0001637668,0.00002040564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005220553,"about_ca_system_score_gemma":0.00008120621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005068947,"about_ca_topic_score_gemma":8.924343e-7,"domain_scores_codex":[0.9983114,0.00005463953,0.0004030459,0.0005790371,0.0003787186,0.0002731609],"domain_scores_gemma":[0.9980291,0.0002463376,0.0001682447,0.0003682848,0.00111606,0.00007195937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000269729,0.00001447646,0.00000318015,0.00001170719,0.00004834882,0.000003062633,0.00200837,0.2760347,0.0004232077,0.7208263,0.000004646252,0.0005950007],"study_design_scores_gemma":[0.0002746993,0.0001096407,0.000009117906,0.0002189401,0.000007850742,0.000006879494,0.004210572,0.9848865,0.0008259962,0.009190054,0.00001239667,0.0002473377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001408209,0.00008460419,0.9941657,0.00003944842,0.002359104,0.0004080102,0.00002745068,0.0007971361,0.000710397],"genre_scores_gemma":[0.6665421,0.000004242336,0.3330858,0.0000140078,0.00008634423,0.0001990273,0.000004864081,0.00001607008,0.00004752096],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7116362,"threshold_uncertainty_score":0.9519808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2800596188748112,"score_gpt":0.3427879297650844,"score_spread":0.0627283108902732,"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."}}