{"id":"W2288393983","doi":"10.1016/j.tcs.2016.01.025","title":"Rendezvous with constant memory","year":2016,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Rendezvous; Constant (computer programming); Robot; Computer science; Asynchronous communication; Transmission (telecommunications); State (computer science); Mobile robot; Theoretical computer science; Algorithm; Artificial intelligence; Computer network; Telecommunications; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001052312,0.0001352363,0.0001383194,0.0001510304,0.0002943418,0.0003194049,0.001972632,0.00002910251,0.0001208693],"category_scores_gemma":[0.00005947828,0.00006889104,0.00002778218,0.0009295258,0.003966326,0.0008097843,0.0006804274,0.00009031622,0.0001553386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005442118,"about_ca_system_score_gemma":0.0002448439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.185632e-7,"about_ca_topic_score_gemma":4.291521e-7,"domain_scores_codex":[0.9977703,0.00008947438,0.0001788193,0.0006237436,0.0007814264,0.0005562451],"domain_scores_gemma":[0.9983278,0.0002255361,0.00004559146,0.0007996049,0.0002591705,0.0003423169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006455982,0.00002504368,0.00002215652,0.000001766318,0.000001995359,0.00001720598,0.0001291342,0.00007285322,0.000614666,0.9249622,0.00006710278,0.07407947],"study_design_scores_gemma":[0.00187285,0.001346983,0.000434791,0.0002017201,0.000005616418,0.0003505897,0.00001343951,0.6336013,0.01859942,0.341669,0.001089502,0.0008147681],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001698195,0.00000861748,0.9732334,0.004831745,0.0001997292,0.0001376423,9.079801e-7,0.0002706767,0.0196191],"genre_scores_gemma":[0.752451,0.000005829063,0.2468346,0.0005896962,0.00003387269,0.000004846841,8.324176e-8,0.000004954954,0.00007514805],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7507528,"threshold_uncertainty_score":0.9987443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009871011720561236,"score_gpt":0.234662408482437,"score_spread":0.2247913967618758,"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."}}