{"id":"W7110076330","doi":"10.4230/lipics.aft.2025.30","title":"Ticket to Ride: Locally Steered Source Routing for the Lightning Network","year":2025,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Traverse; Ticket; Relay; Train; Routing (electronic design automation); Overhead (engineering); Channel (broadcasting); Landmark; Latency (audio)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000787098,0.0003565776,0.0006242111,0.0004953293,0.0006482784,0.0008695567,0.00123314,0.0005634524,0.002355184],"category_scores_gemma":[0.001992373,0.0001423122,0.0002772334,0.0004279194,0.0008010902,0.001693061,0.002015614,0.0007994598,0.0005383454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006283347,"about_ca_system_score_gemma":0.0006359611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001232298,"about_ca_topic_score_gemma":0.00191964,"domain_scores_codex":[0.9995862,0.0001009562,0.00002016587,0.00008168456,0.0001331612,0.00007797325],"domain_scores_gemma":[0.9991966,0.0002224945,0.0001054245,0.0003092641,0.00009210227,0.00007420131],"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":[0.001284516,0.0001865558,0.002530574,0.000335843,0.0001100378,0.0007527955,0.0008583317,0.3132747,0.06107688,0.08277083,0.0177287,0.5190903],"study_design_scores_gemma":[0.00008960736,0.0004955046,0.0004495689,0.00003823885,0.00002973323,0.0004992384,0.0002610832,0.9207418,0.01866429,0.04210189,0.01656673,0.00006228136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09230962,0.0007284335,0.8949964,0.0004399603,0.0001755912,0.0001530887,0.0002443357,0.004865987,0.006086552],"genre_scores_gemma":[0.8812372,0.0002743555,0.1144195,0.0001668832,0.00005417899,0.0000946678,0.0003138956,0.0001272678,0.003311981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002355184,"threshold_uncertainty_score":0.0078789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006985399922941816,"score_gpt":0.2272152971059407,"score_spread":0.2202298971829989,"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."}}