{"id":"W3036156748","doi":"10.1002/spe.2847","title":"Service offloading oriented edge server placement in smart farming","year":2020,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Service (business); Automation; Enhanced Data Rates for GSM Evolution; Server; Agriculture; Edge computing; Distributed computing; Computer network; Telecommunications; Engineering; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002849874,0.000525363,0.0004387063,0.0003244847,0.0007303624,0.0007279689,0.0007695485,0.0006966064,0.00209633],"category_scores_gemma":[0.0006063487,0.0001789155,0.0002211153,0.0005439703,0.0003693024,0.001019628,0.0006710943,0.0003430913,0.000616814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004905641,"about_ca_system_score_gemma":0.000572685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002469811,"about_ca_topic_score_gemma":0.003259669,"domain_scores_codex":[0.9996699,0.00005948654,0.00001461694,0.00008626745,0.00007200158,0.00009769427],"domain_scores_gemma":[0.9996922,0.00007584866,0.00002619743,0.00007988,0.00007386748,0.00005202046],"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":[0.0006821804,0.0003823667,0.003974921,0.0002002343,0.00005481157,0.001394374,0.0003759141,0.5254986,0.1369898,0.0194574,0.01077972,0.3002096],"study_design_scores_gemma":[0.00002198633,0.0001114156,0.001004519,0.000005924729,0.00001065844,0.0001817283,0.0001745436,0.9768737,0.01195687,0.005740843,0.003902716,0.00001501239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2950311,0.0005556617,0.6892605,0.0004050521,0.0002268592,0.0001529115,0.0001284332,0.002267707,0.01197182],"genre_scores_gemma":[0.9175865,0.00015503,0.07893563,0.0001035289,0.00002711237,0.00002616677,0.0001151605,0.00006050975,0.002990341],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002469811,"threshold_uncertainty_score":0.007012904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02779146239554989,"score_gpt":0.2791383117747547,"score_spread":0.2513468493792048,"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."}}