{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":5,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":5,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"d700822e2e69","filters":{"venue":"Software Engineering for Adaptive and Self-Managing Systems"}},"results":[{"id":"W2065358956","doi":"10.5555/2821357.2821365","title":"Towards an autonomic auto-scaling prediction system for cloud resource provisioning","year":2015,"lang":"en","type":"article","venue":"Software Engineering for Adaptive and Self-Managing Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Workload; Computer science; Cloud computing; Benchmark (surveying); Support vector machine; Suite; Data mining; Artificial neural network; Artificial intelligence; Time series; Machine learning; Metric (unit); Provisioning; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01540037666865413,"gpt":0.2148484912666766,"spread":0.1994481145980224,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001598684,0.0003247097,0.0003979729,0.0002678084,0.000360231,0.0004438627,0.0005374969,0.0001129075,3.849042e-8],"category_scores_gemma":[0.0001185879,0.0003143083,0.0001160255,0.0002340064,0.00001617722,0.0001120902,0.0002419051,0.0001464448,0.000001586165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003989316,"about_ca_system_score_gemma":0.00007696328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001021376,"about_ca_topic_score_gemma":8.411195e-7,"domain_scores_codex":[0.9978676,0.00006506254,0.000481023,0.0007468186,0.0002954817,0.0005439664],"domain_scores_gemma":[0.9986395,0.0002343368,0.0001752585,0.0004979828,0.0001746447,0.0002782525],"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":[0.00002337411,0.00004079752,0.00009147739,0.0007884142,0.0001551619,0.000005785032,0.00381319,0.9556417,0.00001505519,0.03146013,0.0004207936,0.007544091],"study_design_scores_gemma":[0.0007852234,0.000402866,0.00009968562,0.0004781507,0.00005058178,0.00003120238,0.001290366,0.9730375,0.00002779314,0.00008694155,0.02336331,0.0003463186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03198295,0.0007751892,0.9608634,0.00005606021,0.001885725,0.001228399,0.00001754853,0.003091108,0.00009968568],"genre_scores_gemma":[0.8935151,0.000001131177,0.1050498,0.00001777116,0.0009111628,0.0002646235,0.00001416908,0.0000665905,0.0001596547],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8615321,"threshold_uncertainty_score":0.9999309,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1976625778","doi":"10.5555/2821357.2821372","title":"Hogna: a platform for self-adaptive applications in cloud environments","year":2015,"lang":"en","type":"article","venue":"Software Engineering for Adaptive and Self-Managing Systems","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Software deployment; Cloud computing; Computer science; Installation; Software; Software engineering; Automation; Plan (archaeology); Set (abstract data type); Distributed computing; Systems engineering; Operating system; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.0364194000861586,"gpt":0.2524406035806636,"spread":0.216021203494505,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008719184,0.0003950583,0.0004970218,0.0003169352,0.0001274254,0.0001044796,0.0005482059,0.0001474097,6.001246e-8],"category_scores_gemma":[0.0003731096,0.0004063424,0.0000972034,0.0003606842,0.00002460793,0.0006210349,0.000194845,0.0001995177,0.000002381392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004077176,"about_ca_system_score_gemma":0.00005682322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002615924,"about_ca_topic_score_gemma":0.000002663666,"domain_scores_codex":[0.9979924,0.00003564233,0.000414392,0.0006901938,0.0002442636,0.0006231088],"domain_scores_gemma":[0.9974838,0.001610134,0.0001354115,0.0004774315,0.00008598958,0.000207265],"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":[0.00004339309,0.0001549586,0.0005418023,0.0005424641,0.0002936507,0.0000100726,0.005125403,0.8619744,0.00004238889,0.1275072,0.0001857573,0.003578514],"study_design_scores_gemma":[0.002737635,0.0008206409,0.0006597056,0.000333796,0.00008576243,0.00003909193,0.001316936,0.9321221,0.0002205195,0.01390674,0.04628997,0.001467166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009360579,0.002210307,0.992623,0.00001887289,0.0007296955,0.001960367,0.00003322529,0.001475093,0.00001333875],"genre_scores_gemma":[0.1089542,0.00005222794,0.8886064,0.00001388606,0.0001971698,0.002016042,0.00001504476,0.00007055762,0.00007448877],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1136005,"threshold_uncertainty_score":0.9998388,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2085367298","doi":"10.5555/2821357.2821380","title":"Adaptive management of energy consumption using adaptive runtime models","year":2015,"lang":"en","type":"article","venue":"Software Engineering for Adaptive and Self-Managing Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Energy consumption; Feature extraction; Data mining; Scheduling (production processes); Classifier (UML); Energy management; Schedule; Artificial intelligence; Data center; Adaptive control; Machine learning; Real-time computing; Energy (signal processing); Control (management); Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03593370415906915,"gpt":0.2237523495000302,"spread":0.1878186453409611,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005952985,0.0003572531,0.0004671745,0.0003296238,0.0001489165,0.0001080539,0.000482325,0.00008931874,2.220876e-7],"category_scores_gemma":[0.00001151283,0.0003588308,0.0001238313,0.0003397396,0.00003981949,0.000122238,0.0004474303,0.0001112537,0.000001696516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002135686,"about_ca_system_score_gemma":0.00003249227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000228053,"about_ca_topic_score_gemma":0.000001475971,"domain_scores_codex":[0.9979416,0.00006508821,0.0004521083,0.0006288459,0.0004290264,0.0004832929],"domain_scores_gemma":[0.9987216,0.0001660081,0.0002363489,0.0004529149,0.0002329443,0.0001901614],"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":[0.00002612199,0.00005559914,0.00004597399,0.000276789,0.0004554979,0.00001778372,0.0009224958,0.8198987,0.000004179842,0.17619,0.000084557,0.002022329],"study_design_scores_gemma":[0.000755295,0.0002676632,0.00006859659,0.0005820761,0.000104677,0.00002029159,0.0005645558,0.9953933,0.00002330012,0.001224774,0.0005939389,0.0004015294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01431215,0.002843966,0.9808047,0.00001339906,0.0006049111,0.0005389152,0.00001026902,0.0006055665,0.0002660798],"genre_scores_gemma":[0.7978274,0.00002501317,0.2017882,0.00001248354,0.00009090817,0.00006186649,0.00000260001,0.00003845253,0.0001531275],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7835152,"threshold_uncertainty_score":0.9998864,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2083644481","doi":"10.5555/2663546.2663574","title":"RPC automation: making legacy code relevant","year":2013,"lang":"en","type":"article","venue":"Software Engineering for Adaptive and Self-Managing Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Remote procedure call; Automation; Legacy system; Locality; Distributed computing; Profiling (computer programming); Component (thermodynamics); Legacy code; Code (set theory); Process (computing); Embedded system; Software engineering; Software; Operating system; Programming language; Set (abstract data type)","retraction":null,"screen_n_in":null,"score":{"opus":0.01035498058526691,"gpt":0.2085089952561925,"spread":0.1981540146709256,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003637465,0.0002504174,0.0002723931,0.0002071093,0.0002573508,0.0006373134,0.000449162,0.0000621236,9.400786e-7],"category_scores_gemma":[0.00007099733,0.0002339829,0.00008448683,0.0002595134,0.00001434391,0.0001438717,0.0002516304,0.0001304811,0.0000200495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009484783,"about_ca_system_score_gemma":0.00001639277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008476563,"about_ca_topic_score_gemma":0.00000124965,"domain_scores_codex":[0.9984747,0.00003212429,0.0003225817,0.0004851421,0.0002417937,0.000443652],"domain_scores_gemma":[0.9989733,0.0002905829,0.0001159386,0.0004102443,0.0001128932,0.00009709827],"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":[0.000005046759,0.00009789477,0.0006285391,0.001507482,0.0004786921,0.00003188452,0.004632061,0.7802337,0.00005311051,0.1750653,0.004226729,0.03303947],"study_design_scores_gemma":[0.0002544601,0.0000818246,0.001143483,0.000311149,0.00001785868,0.00002577992,0.0001841467,0.9809264,0.000006680605,0.0003025018,0.01643323,0.0003124921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02298913,0.001021936,0.9718721,0.0002877551,0.0008378419,0.0007381521,0.000002108003,0.002058804,0.0001921615],"genre_scores_gemma":[0.8756873,0.00000524047,0.1234439,0.00005762792,0.0002312225,0.0001680117,0.000001715562,0.00003396786,0.0003710765],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8526981,"threshold_uncertainty_score":0.9541546,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1989585025","doi":"10.5555/2666795.2666809","title":"A middleware and algorithms for trust calculation from multiple evidence sources","year":2012,"lang":"en","type":"article","venue":"Software Engineering for Adaptive and Self-Managing Systems","topic":"Access Control and Trust","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Computer science; Middleware (distributed applications); Computational trust; Algorithm; Distributed computing; Data mining; Theoretical computer science; Reputation","retraction":null,"screen_n_in":null,"score":{"opus":0.03864106244420128,"gpt":0.2725084112145675,"spread":0.2338673487703662,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006087972,0.000176432,0.0002721426,0.00008484536,0.0005052779,0.0001666466,0.000107507,0.0001072638,0.000001044037],"category_scores_gemma":[0.0007045893,0.0001691729,0.0000677955,0.0001015941,0.00004499911,0.0006746855,0.00003213515,0.0000709967,9.97275e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007234395,"about_ca_system_score_gemma":0.00002258108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003428812,"about_ca_topic_score_gemma":0.0001255358,"domain_scores_codex":[0.9988712,0.00004372828,0.0002030057,0.0002695925,0.000180949,0.0004315356],"domain_scores_gemma":[0.9978933,0.001628295,0.00009296762,0.0001003107,0.0001105805,0.0001745954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002660854,0.0002078951,0.7898633,0.002260361,0.001292862,0.000005302826,0.1100126,0.01529408,0.0001508448,0.04105645,0.0006796562,0.03891048],"study_design_scores_gemma":[0.002547706,0.0002347722,0.07450958,0.001320492,0.0004893357,0.000004998528,0.01325641,0.7851918,0.00004838115,0.0004967847,0.1205703,0.001329381],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.128655,0.02270912,0.8455557,0.000103786,0.0008978354,0.001454213,0.0001181838,0.000481713,0.0000244913],"genre_scores_gemma":[0.984213,0.0001321612,0.0141831,0.00001436835,0.0009535889,0.0003021282,0.00001540605,0.00002893027,0.0001573281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.855558,"threshold_uncertainty_score":0.6898671,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}