{"id":"W2601874932","doi":"10.5539/ass.v13n4p162","title":"Financial Incentives for Adopting Cloud Computing in Higher Educational Institutions","year":2017,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cloud computing; Incentive; Flexibility (engineering); Government (linguistics); Computer science; Finance; Service (business); Cloud computing security; Cost reduction; Institution; Financial institution; Utility computing; Business; Environmental economics; Computer security; Economics; Marketing; Management; Microeconomics; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01248898,0.0001559029,0.0001987739,0.001135888,0.004189232,0.005660794,0.0006847787,0.002436417,0.004540895],"category_scores_gemma":[0.03938347,0.0003077513,0.0002677249,0.001452514,0.002183683,0.001912179,0.002533379,0.002211356,0.0002928913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007935092,"about_ca_system_score_gemma":0.01240323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006130177,"about_ca_topic_score_gemma":0.01088539,"domain_scores_codex":[0.9841709,0.008766528,0.0007060887,0.0003118068,0.002186396,0.003858289],"domain_scores_gemma":[0.9039986,0.04305382,0.02916956,0.001621354,0.006769964,0.01538674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009044787,0.001835073,0.62705,0.0005487044,0.0001001032,0.002581549,0.01529176,0.00848511,0.004849933,0.2249072,0.01061722,0.1028289],"study_design_scores_gemma":[0.0002718206,0.000958085,0.7986781,0.00111153,0.0001144264,0.001330757,0.06283892,0.01644976,0.003836598,0.04427883,0.06979835,0.0003328387],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9229417,0.0004403895,0.002732166,0.01438856,0.00007122911,0.0002947852,0.0001004563,0.00002590569,0.05900475],"genre_scores_gemma":[0.998551,0.00006805428,0.0004397128,0.0003584617,0.00001570622,0.00002894796,0.000008865414,0.000001526921,0.0005277746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01248898,"threshold_uncertainty_score":0.0660488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04516005218284085,"score_gpt":0.3227405738453621,"score_spread":0.2775805216625213,"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."}}