{"id":"W4404400709","doi":"10.1145/3694715.3695954","title":"Caribou: Fine-Grained Geospatial Shifting of Serverless Applications for Sustainability","year":2024,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Alliance de recherche numérique du Canada; Institute for Computing, Information and Cognitive Systems; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Geospatial analysis; Sustainability; Computer science; Environmental science; Remote sensing; Geography; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000430264,0.00008627078,0.0001160186,0.00007503148,0.0001078434,0.0001165214,0.0005339794,0.00003013371,0.000004253266],"category_scores_gemma":[0.00003693742,0.00007203202,0.0001123224,0.0004093482,0.0000276155,0.00001850173,0.0003586229,0.00005688192,0.000002480648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006066272,"about_ca_system_score_gemma":0.0000753308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002263795,"about_ca_topic_score_gemma":0.00005683695,"domain_scores_codex":[0.9990612,0.00002324634,0.0002277917,0.0003429683,0.0001454326,0.0001993561],"domain_scores_gemma":[0.999144,0.0002051793,0.00003829845,0.0004318687,0.0001405792,0.0000401123],"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":[0.000003130056,0.00008157687,0.0003924571,0.0008504078,0.00004418374,0.000002252753,0.001087567,0.006854155,0.00002811903,0.74861,0.0008662887,0.2411798],"study_design_scores_gemma":[0.0001600396,0.0000540708,0.0006454657,0.00002481476,0.00001418217,0.000001123032,0.0001812969,0.940191,0.0003173333,0.03422841,0.02405046,0.0001318243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04695788,0.00009876632,0.9477176,0.002922492,0.0001412881,0.0006120089,0.000004500139,0.000329276,0.00121616],"genre_scores_gemma":[0.9810457,2.428488e-7,0.01765794,0.00004281636,0.0001045037,0.0001095258,0.000004347561,0.000006517797,0.001028428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9340878,"threshold_uncertainty_score":0.293738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009876239239704435,"score_gpt":0.2632991040390051,"score_spread":0.2534228647993007,"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."}}