{"id":"W1534792468","doi":"10.1007/978-3-642-11723-7_16","title":"DHT-Based Detection of Node Clone in Wireless Sensor Networks","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wireless sensor network; Computer science; Computer network; clone (Java method); Node (physics); Engineering; Biology; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004395114,0.0002878752,0.0004697307,0.0003171501,0.0004285704,0.0001244001,0.002047415,0.0004354739,4.248854e-7],"category_scores_gemma":[0.00004370475,0.000255566,0.0001966896,0.0003779347,0.0005141619,0.0002615316,0.0005508675,0.0008596274,1.918372e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006327034,"about_ca_system_score_gemma":0.0001310068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007003776,"about_ca_topic_score_gemma":0.0003320041,"domain_scores_codex":[0.9984645,0.0000175992,0.0007889188,0.0001821156,0.0002784663,0.0002684243],"domain_scores_gemma":[0.9977935,0.0005255092,0.0006521243,0.000792979,0.0001916878,0.00004418276],"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":[0.000002359081,0.00001541653,0.000006160397,0.0001249781,0.00002509875,1.068436e-7,0.000507598,0.9734225,0.0001451672,0.0115523,0.000002178131,0.01419609],"study_design_scores_gemma":[0.0002458613,0.00004788376,0.00005595231,0.0002563241,0.00002043197,0.000006537067,0.000001757385,0.9962817,0.001160687,0.0003335946,0.00133173,0.0002575604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002369635,0.0001996841,0.9953895,0.0003702825,0.0008283152,0.0004695254,0.00001995503,0.00005829959,0.0002947542],"genre_scores_gemma":[0.2671173,0.0000745018,0.7325168,0.0001148107,0.0001236561,0.00001491357,0.00001533444,0.0000168065,0.000005795215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2647477,"threshold_uncertainty_score":0.9999896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451219267237206,"score_gpt":0.2212275483243667,"score_spread":0.2067153556519946,"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."}}