{"id":"W2040855320","doi":"10.1109/iwcmc.2013.6583748","title":"A recursive solution for improving the synchronization accuracy in wireless sensor networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Network Time Synchronization Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Synchronization (alternating current); Flexibility (engineering); Convergence (economics); Distributed computing; Stability (learning theory); Clock synchronization; Wireless sensor network; Simple (philosophy); Protocol (science); Core (optical fiber); Mathematical optimization; Computer network; Channel (broadcasting); Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002783407,0.0001364665,0.0001241852,0.0001029063,0.0002061713,0.0002722243,0.0008247123,0.0001258933,0.00002707104],"category_scores_gemma":[0.0003740242,0.00009900076,0.00003870041,0.0008157159,0.00006867055,0.0009472502,0.0002822031,0.0001471373,0.00003873426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001608288,"about_ca_system_score_gemma":0.00006353724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001381432,"about_ca_topic_score_gemma":0.00005447783,"domain_scores_codex":[0.998781,0.0000623895,0.0002744129,0.0003559085,0.0001332732,0.0003930063],"domain_scores_gemma":[0.9984605,0.0005812725,0.0001657146,0.0005387419,0.0002255127,0.0000282674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000291928,0.00003309662,0.0005588553,0.00001791985,0.000008970124,7.532659e-7,0.000204341,0.01695657,0.0004331981,0.0732232,0.007047274,0.9015129],"study_design_scores_gemma":[0.0002392602,0.00003994927,0.0005303169,0.00001504786,0.000002591501,0.000003771174,0.00007278335,0.9933044,0.0006579635,0.004829272,0.0001638171,0.0001408532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002109352,0.0001144711,0.9907071,0.004949091,0.0002527573,0.001223366,3.588851e-7,0.0004693515,0.0001741321],"genre_scores_gemma":[0.9129785,0.00002694214,0.08596597,0.0003859065,0.00009592361,0.0003263301,0.000006309413,0.00001376144,0.0002003259],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9763478,"threshold_uncertainty_score":0.4037134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009494430145619702,"score_gpt":0.2212021766369942,"score_spread":0.2117077464913745,"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."}}