{"id":"W2097422349","doi":"10.1109/mcom.2011.5741143","title":"GRS: The green, reliability, and security of emerging machine to machine communications","year":2011,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":253,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; University of Ottawa; University of Waterloo","funders":"","keywords":"Machine to machine; Computer science; Control communications; Scheduling (production processes); Communications security; Efficient energy use; Communications system; Redundancy (engineering); Software deployment; Automation; Reliability (semiconductor); Wireless sensor network; Computer security; Computer network; Telecommunications; Internet of Things; Engineering","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":[0.00237599,0.0006598416,0.0006701963,0.0008661576,0.001165971,0.003484549,0.001539017,0.002562047,0.001882124],"category_scores_gemma":[0.004346086,0.0004752373,0.0004887618,0.0007968302,0.003513237,0.005838928,0.002239746,0.002237107,0.0005868381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001375653,"about_ca_system_score_gemma":0.001434995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329176,"about_ca_topic_score_gemma":0.001221865,"domain_scores_codex":[0.997542,0.0007071705,0.0001384584,0.0002981833,0.001061653,0.0002525104],"domain_scores_gemma":[0.9960985,0.001757043,0.0004315146,0.0007616073,0.0007742444,0.0001770488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007377988,0.00003072941,0.0006870659,0.000314053,0.00002438836,0.0003497541,0.0003261637,0.02108384,0.007966367,0.8949924,0.005606787,0.0685447],"study_design_scores_gemma":[0.00003996684,0.0002523899,0.001597262,0.0003450644,0.00004267178,0.001561251,0.0005125229,0.1821997,0.01185256,0.6604102,0.1410981,0.00008827728],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02866652,0.008058698,0.9021829,0.01109192,0.000675523,0.0001404461,0.0001291885,0.0006390961,0.04841574],"genre_scores_gemma":[0.7886038,0.008471144,0.1911171,0.001588364,0.001384894,0.0002325321,0.0001212251,0.0001396029,0.008341206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003484549,"threshold_uncertainty_score":0.01256561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05097035117261643,"score_gpt":0.2952244186531108,"score_spread":0.2442540674804944,"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."}}