{"id":"W2616626961","doi":"10.1145/384268.378836","title":"Online prediction of the running time of tasks","year":2001,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Computer science; Running time; Algorithm","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":[0.002721182,0.0000983741,0.0002892843,0.0001893498,0.00009736545,0.00001503704,0.0009684773,0.00003578613,0.0002380686],"category_scores_gemma":[0.001536755,0.00006701117,0.0001421417,0.004312554,0.0000355936,0.0004237721,0.0002910075,0.0001016969,0.0000149594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000427103,"about_ca_system_score_gemma":0.00009517192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006427726,"about_ca_topic_score_gemma":7.384492e-7,"domain_scores_codex":[0.9980223,0.00009752161,0.0006672352,0.0001906848,0.0008887918,0.0001334879],"domain_scores_gemma":[0.997561,0.000107721,0.0006781494,0.0009620604,0.0006629229,0.0000281657],"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":[0.000001831768,0.00008213421,0.01993038,0.0004525009,0.00003405785,9.976237e-8,0.00009535319,0.002557191,0.0002513171,0.0001349297,0.0008267605,0.9756334],"study_design_scores_gemma":[0.0002085954,0.0001126603,0.09285431,0.001552109,0.0001845561,0.000008818715,0.000008853765,0.898098,0.0004597339,0.00006021586,0.006358047,0.00009411685],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8333266,0.1308619,0.02701857,0.002198966,0.0006702466,0.001774787,0.00002674099,0.0001021041,0.004020052],"genre_scores_gemma":[0.931536,0.05545152,0.01222797,0.0003624499,0.00007970211,0.00002154921,0.00003730118,0.00001099904,0.0002725713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9755393,"threshold_uncertainty_score":0.2732636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07124270300972026,"score_gpt":0.3028269319459966,"score_spread":0.2315842289362764,"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."}}