{"id":"W3191242629","doi":"10.1007/978-3-030-89240-1_6","title":"Evacuating from $$\\ell _p$$ Unit Disks in the Wireless Model","year":2021,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Unit disk; Homogeneous space; Metric (unit); Metric space; Combinatorics; Mathematics; Circumference; Upper and lower bounds; Regular polygon; Euclidean space; Type (biology); Unit (ring theory); Chord (peer-to-peer); Unit sphere; Euclidean geometry; Wireless; Space (punctuation); Computer science; Discrete mathematics; Geometry; Mathematical analysis; Engineering; Distributed computing","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","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.002135994,0.0003884346,0.0004203552,0.0004624469,0.000276064,0.002405589,0.007131781,0.000254106,0.00001085749],"category_scores_gemma":[0.0002278244,0.0002997892,0.0001029312,0.002724248,0.0003351264,0.0006775362,0.005186635,0.001776194,0.000006500391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001680463,"about_ca_system_score_gemma":0.001220752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005371989,"about_ca_topic_score_gemma":0.0006569637,"domain_scores_codex":[0.9952579,0.0004551827,0.0005617531,0.001666312,0.001309382,0.0007494465],"domain_scores_gemma":[0.9965183,0.0008740534,0.0002047867,0.00199996,0.0002770948,0.0001257872],"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":[0.000001219372,0.00006436087,0.0006817202,0.00001882957,0.000002924503,0.00003373069,0.009714715,0.8868229,0.0001574533,0.0003972081,0.000003932076,0.102101],"study_design_scores_gemma":[0.0002086213,0.00002089546,0.0008559962,0.0002878393,0.000002262381,0.000005776315,0.000007479051,0.9663175,0.000835504,0.03110758,0.000004746039,0.0003458034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06004946,0.0002049363,0.9352788,0.003016204,0.0008097859,0.0004635495,0.000005368078,0.00009378524,0.00007809597],"genre_scores_gemma":[0.5998337,0.00003362457,0.3984263,0.001566511,0.00008858206,0.00002806054,0.00001282858,0.000009262475,0.000001158651],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5397843,"threshold_uncertainty_score":0.9999454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05171197795241873,"score_gpt":0.3083168708863218,"score_spread":0.256604892933903,"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."}}