{"id":"W2956038886","doi":"10.23977/acss.2019.31002","title":"Research on WSN Secure Communication Method Based on Digital Watermark for the Monitoring of Electric Transmission Lines","year":2019,"lang":"en","type":"article","venue":"Advances in Computer Signals and Systems","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Wireless sensor network; Electric power transmission; Transmission (telecommunications); Overhead (engineering); Data transmission; Authentication (law); Key distribution in wireless sensor networks; Real-time computing; Sensor node; Node (physics); Computer network; Wireless; Embedded system; Electrical engineering; Engineering; Telecommunications; Wireless network; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006797641,0.00008664846,0.0001634217,0.000113599,0.00007054304,0.00005718588,0.0002114713,0.0000520999,5.985556e-7],"category_scores_gemma":[0.000005779991,0.00005473817,0.00003199398,0.0001950026,0.00001794208,0.0001474435,0.00001405999,0.0001783413,0.000001040442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001652214,"about_ca_system_score_gemma":0.000007010387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006102833,"about_ca_topic_score_gemma":5.055313e-7,"domain_scores_codex":[0.9991889,0.0001161009,0.0002041835,0.0001349108,0.0001964549,0.0001594402],"domain_scores_gemma":[0.9976874,0.001990656,0.00002786984,0.0002164391,0.00005356368,0.00002405711],"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":[0.00005319577,0.00002246838,0.001109797,0.0003840046,0.000006301502,3.594222e-7,0.000298252,0.9518767,0.001063708,0.0001405997,0.00002468117,0.04501996],"study_design_scores_gemma":[0.0002640627,0.0002186231,0.000533025,0.0007327175,0.000001676896,0.000001065053,0.00008865998,0.9882831,0.005706444,0.00008605022,0.004012308,0.00007227996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4141825,0.02398155,0.5591806,0.00009252234,0.001081556,0.001123157,0.000009921552,0.00005300745,0.0002952301],"genre_scores_gemma":[0.9973902,0.00107187,0.00133769,0.000005281328,0.0001360332,0.00003800387,0.000002542975,0.00000992131,0.000008449436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5832077,"threshold_uncertainty_score":0.2232158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02693856033299469,"score_gpt":0.3310413617114735,"score_spread":0.3041028013784788,"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."}}