{"id":"W2136757130","doi":"10.1109/percom.2009.4912893","title":"Key predistribution scheme using keyed-hash chain and multipath key reinforcement for wireless sensor networks","year":2009,"lang":"en","type":"article","venue":"","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University; Acadia University","funders":"","keywords":"Computer science; Hash chain; Hash function; Computer network; Wireless sensor network; Key (lock); Cryptographic hash function; Key generation; Multipath propagation; Key space; Node (physics); Distributed computing; Computer security; Encryption; Channel (broadcasting); 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004612949,0.0003282405,0.0003477498,0.00009449863,0.0003548578,0.0003272191,0.0005254556,0.0002440846,0.000007849286],"category_scores_gemma":[0.00005063586,0.0003249788,0.0001050485,0.0003573668,0.00007367893,0.0005255002,0.0001979201,0.0002379214,0.000003511612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001577417,"about_ca_system_score_gemma":0.00004500538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004562418,"about_ca_topic_score_gemma":0.00001128373,"domain_scores_codex":[0.9976305,0.00006358159,0.0004902439,0.0006830083,0.0003497522,0.0007829645],"domain_scores_gemma":[0.9985291,0.0001694435,0.0002010596,0.0006573871,0.000211744,0.0002312353],"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":[0.0003364012,0.0005861727,0.001986607,0.0001641467,0.0002050344,0.00006750031,0.004116251,0.4597425,0.01787865,0.4189915,0.006014965,0.08991031],"study_design_scores_gemma":[0.001088744,0.0002009691,0.0003844552,0.00007026498,0.0000135105,0.00002985027,0.00006331407,0.994754,0.001712881,0.0004376029,0.0008469176,0.0003974698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1714911,0.0001641417,0.8261093,0.0005314636,0.0003701382,0.000756412,0.000006956198,0.0003310372,0.0002394309],"genre_scores_gemma":[0.8542695,0.00006224009,0.1445438,0.000552981,0.0003680208,0.00001973083,0.00004021484,0.00001675015,0.0001266932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6827784,"threshold_uncertainty_score":0.9999202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940873611094731,"score_gpt":0.2554770365311719,"score_spread":0.2360683004202246,"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."}}