{"id":"W2745255568","doi":"10.1002/ett.3223","title":"MABO‐TSCH: Multihop and blacklist‐based optimized time synchronized channel hopping","year":2017,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Federation for the Humanities and Social Sciences; Horizon 2020 Framework Programme; Institut national de recherche en informatique et en automatique (INRIA); National Science Foundation","keywords":"Frequency-hopping spread spectrum; Computer science; Testbed; Blacklisting; Blacklist; Computer network; Transmitter; Robustness (evolution); Spread spectrum; Network packet; Channel (broadcasting); Wireless; Real-time computing; Computer security; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004370525,0.000376812,0.0004465084,0.0005454874,0.0004317088,0.0004381381,0.0008509844,0.0004301786,0.001295173],"category_scores_gemma":[0.001230003,0.0001418445,0.0001674141,0.0003063321,0.0004285374,0.0004703962,0.0007550116,0.0003172341,0.000203792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003316986,"about_ca_system_score_gemma":0.0007472368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001693373,"about_ca_topic_score_gemma":0.002484704,"domain_scores_codex":[0.9997757,0.00005846273,0.000007833552,0.00004382048,0.00006917018,0.00004501565],"domain_scores_gemma":[0.9993259,0.0002953445,0.0001129663,0.00008111956,0.0001075327,0.00007723442],"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":[0.0005022433,0.000208806,0.001834825,0.00006759289,0.00006070972,0.000127543,0.000127265,0.8032048,0.02396889,0.007042831,0.002720786,0.1601337],"study_design_scores_gemma":[0.00003032968,0.00007353161,0.0001676489,0.000002857014,0.000005055804,0.00002219978,0.00001244324,0.9962415,0.002118535,0.0009183662,0.0004011022,0.000006558127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1934272,0.0003658193,0.7997804,0.0002178206,0.0001664571,0.0001144107,0.00006741617,0.001600376,0.004260181],"genre_scores_gemma":[0.9446546,0.00004829435,0.05366517,0.00006246453,0.00002098879,0.00004786874,0.00004572601,0.00002969535,0.001425248],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001693373,"threshold_uncertainty_score":0.004332781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01812196890637686,"score_gpt":0.2578540222307774,"score_spread":0.2397320533244005,"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."}}