{"id":"W1926766979","doi":"10.1002/wcm.2258","title":"Smart grid sensor data collection, communication, and networking: a tutorial","year":2012,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Nanyang Technological University","keywords":"Smart grid; Computer science; Standardization; Data collection; Grid; Telecommunications network; Wireless sensor network; Context (archaeology); Distributed computing; Telecommunications; Computer network; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005316741,0.0001425401,0.000181649,0.00006169598,0.0008826639,0.000100199,0.000721238,0.00008471777,0.000003535714],"category_scores_gemma":[0.00001579605,0.0001503885,0.00001767226,0.0002636779,0.0002399829,0.000276802,0.001174398,0.0003084105,0.000003703171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002720689,"about_ca_system_score_gemma":0.00001673568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008286932,"about_ca_topic_score_gemma":0.00005421338,"domain_scores_codex":[0.9990531,0.0001357169,0.0002805529,0.0001630449,0.00009091909,0.0002767317],"domain_scores_gemma":[0.997564,0.0004287032,0.00005839753,0.001768742,0.0000568992,0.0001232229],"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":[0.00005322534,0.001034652,0.2775296,0.0006795331,0.0006210376,0.000002462952,0.04872389,0.005439042,0.003041492,0.01289789,0.04524725,0.60473],"study_design_scores_gemma":[0.0003095586,0.00001736367,0.004623801,0.00009484454,0.00002951503,0.00005043505,0.0007285699,0.5808598,0.00004106118,0.00002748533,0.4129579,0.0002596035],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9232174,0.06405427,0.006505882,0.0002980796,0.002335294,0.0006368487,0.00003014921,0.0005932554,0.002328879],"genre_scores_gemma":[0.9803117,0.01373353,0.005203195,0.00003380843,0.00052895,0.00002625744,0.0001218032,0.00002238652,0.00001839186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6044703,"threshold_uncertainty_score":0.6788827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02748863634154529,"score_gpt":0.2620303383326831,"score_spread":0.2345417019911378,"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."}}