{"id":"W2603214747","doi":"10.1142/s012905411750006x","title":"Deterministic Rendezvous with Detection Using Beeps","year":2017,"lang":"en","type":"article","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Computer science; Node (physics); Mobile agent; Computer network; Real-time computing; Distributed computing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001210813,0.00121536,0.00130202,0.0007106593,0.001215956,0.001947081,0.00295399,0.001848286,0.004271036],"category_scores_gemma":[0.006601238,0.0007484751,0.001144807,0.0008231225,0.00203492,0.003008209,0.003965152,0.001979413,0.0009114675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001489437,"about_ca_system_score_gemma":0.001293175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004851278,"about_ca_topic_score_gemma":0.004416908,"domain_scores_codex":[0.9976184,0.0005366655,0.0001306613,0.0005863431,0.0006731763,0.0004547718],"domain_scores_gemma":[0.9950352,0.002687025,0.0005419824,0.001075595,0.0004083781,0.0002518152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004199674,0.00008182196,0.001251943,0.0002534831,0.0000823064,0.0005404186,0.0004712908,0.6230657,0.01100481,0.3226392,0.003710754,0.03647839],"study_design_scores_gemma":[0.00004366085,0.00005963203,0.0001092155,0.00001507872,0.00001864728,0.000123509,0.00004195021,0.927904,0.002787811,0.06455946,0.004301586,0.00003548347],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01729153,0.0002611352,0.9740627,0.0002301086,0.00007264878,0.00008612146,0.0001193264,0.0007205067,0.007155845],"genre_scores_gemma":[0.8204774,0.0004321857,0.1651019,0.000276198,0.00007257083,0.0004290337,0.0002695876,0.000226568,0.0127146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004851278,"threshold_uncertainty_score":0.01428801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04234109411602974,"score_gpt":0.3511103756066453,"score_spread":0.3087692814906156,"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."}}