{"id":"W2241158615","doi":"10.1109/cccs.2015.7374135","title":"Comparative study of Wireless Sensor Network standards for application in Electrical Substations","year":2015,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Wireless sensor network; 6LoWPAN; Robustness (evolution); Flexibility (engineering); Software deployment; Physical layer; Computer science; Wireless; Key distribution in wireless sensor networks; Grid; Computer network; Embedded system; Engineering; Wireless network; Telecommunications","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":[0.003100493,0.0003118731,0.0002761132,0.002916453,0.0002782036,0.001026837,0.0005692819,0.0005713459,0.00118359],"category_scores_gemma":[0.006515017,0.0001171644,0.0003727894,0.004385584,0.0002373577,0.001772144,0.0004181482,0.0004074311,0.0003965593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006534602,"about_ca_system_score_gemma":0.0008157864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009161461,"about_ca_topic_score_gemma":0.001090839,"domain_scores_codex":[0.9974632,0.0006087303,0.0003688815,0.000273275,0.001138345,0.0001475792],"domain_scores_gemma":[0.9938758,0.002195174,0.0004576539,0.0001916337,0.003131726,0.0001479036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004578698,0.0001499637,0.02442173,0.004314275,0.0001177971,0.0004165483,0.0006862587,0.008622665,0.02181582,0.02384458,0.009630678,0.9055218],"study_design_scores_gemma":[0.00004965517,0.002336186,0.1189134,0.002740282,0.0005548738,0.004224932,0.003430665,0.02845303,0.04932749,0.009821801,0.7799737,0.0001739751],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3486003,0.3738384,0.1277853,0.004626803,0.002232591,0.0004809042,0.001813118,0.0006303596,0.1399923],"genre_scores_gemma":[0.7469881,0.1946852,0.04413565,0.0008099214,0.0007117881,0.0002796618,0.002478471,0.000152294,0.009758973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003100493,"threshold_uncertainty_score":0.01639718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04474972524543089,"score_gpt":0.3309386147589459,"score_spread":0.286188889513515,"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."}}