{"id":"W1766799846","doi":"10.23638/dmtcs-22-4-4","title":"Evacuating Robots from a Disk Using Face-to-Face Communication","year":2020,"lang":"en","type":"preprint","venue":"Discrete Mathematics & Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Unit disk; Approx; Upper and lower bounds; Face (sociological concept); Boundary (topology); Computer science; Unit (ring theory); Algorithm; Combinatorics; Mathematics; Artificial intelligence; Mathematical analysis; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008576215,0.0009450178,0.0008479951,0.0004348,0.001462278,0.0009446038,0.002923273,0.001991744,0.007655576],"category_scores_gemma":[0.00506429,0.0003972402,0.0008639391,0.0005609695,0.001394907,0.003260768,0.00325266,0.001937003,0.002881036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009213915,"about_ca_system_score_gemma":0.0008191948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002655329,"about_ca_topic_score_gemma":0.003733701,"domain_scores_codex":[0.9990953,0.0002170961,0.00005232435,0.0002364647,0.0002238912,0.0001749892],"domain_scores_gemma":[0.9974879,0.001255122,0.000219214,0.0006286869,0.0002538354,0.0001550847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003043693,0.0003479061,0.004597386,0.001370149,0.0001357645,0.001716965,0.002065131,0.5317238,0.03664391,0.128849,0.04281767,0.2466887],"study_design_scores_gemma":[0.0002149171,0.0004814147,0.00123848,0.0001328729,0.00004664458,0.001236626,0.001300269,0.8405063,0.05339832,0.06584866,0.03548817,0.0001072771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1141989,0.0005427744,0.8544178,0.003494052,0.0002525101,0.0002929451,0.0003666195,0.002726493,0.02370796],"genre_scores_gemma":[0.5158733,0.0004009087,0.4692358,0.0006871913,0.00005913962,0.0002515232,0.0005816286,0.0002560671,0.01265452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007655576,"threshold_uncertainty_score":0.02561051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05559212295919166,"score_gpt":0.3286861245468449,"score_spread":0.2730940015876533,"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."}}