{"id":"W2146411427","doi":"10.1109/wcnc.2005.1424575","title":"A clock-sampling mutual network time-synchronization algorithm for wireless ad hoc networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Network Time Synchronization Technologies","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Wireless ad hoc network; Beacon; Scalability; Computer network; Robustness (evolution); Wireless sensor network; Overhead (engineering); Wireless network; Clock synchronization; Synchronization (alternating current); Data synchronization; Algorithm; Wireless; Real-time computing; Telecommunications","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":[0.0004651885,0.0003352398,0.0003417978,0.0001392633,0.0004463732,0.0003348627,0.001365942,0.0003054033,0.0001384542],"category_scores_gemma":[0.00004343907,0.0003318482,0.0001186675,0.001307393,0.00009966278,0.0008431972,0.0005194656,0.0002258175,0.0002483687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002293225,"about_ca_system_score_gemma":0.0001164324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001202939,"about_ca_topic_score_gemma":0.00001211058,"domain_scores_codex":[0.997431,0.0000549029,0.0005314171,0.000767145,0.0003103746,0.0009051306],"domain_scores_gemma":[0.9982237,0.0003017958,0.0002290247,0.0008521468,0.0002743467,0.0001190285],"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":[0.00000296369,0.00003092383,0.00001646374,0.000003762111,0.00002349712,7.990587e-7,0.0000348831,0.1714315,0.000006879759,0.009435625,0.01700076,0.8020119],"study_design_scores_gemma":[0.0005058056,0.0001161809,0.00001666698,0.00003079291,0.00001143452,0.00001113278,0.000008885272,0.9225137,0.0001840105,0.001559045,0.07464908,0.0003933166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001120671,0.002952392,0.991643,0.001116093,0.0004725195,0.0006872943,0.000003044074,0.002492861,0.00052069],"genre_scores_gemma":[0.01693847,0.0003934127,0.9775066,0.000672432,0.001416967,0.0001391199,0.00006359712,0.00005873875,0.002810697],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8016186,"threshold_uncertainty_score":0.9999133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01058124223492748,"score_gpt":0.2336960593311698,"score_spread":0.2231148170962423,"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."}}