{"id":"W4312532973","doi":"10.1007/978-3-031-22050-0_6","title":"Triangle Evacuation of 2 Agents in the Wireless Model","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Equilateral triangle; Combinatorics; Perimeter; Mathematics; Point (geometry); Infimum and supremum; Enhanced Data Rates for GSM Evolution; Square (algebra); Unit square; Incircle and excircles of a triangle; Upper and lower bounds; Computer science; Discrete mathematics; Geometry; Artificial intelligence","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":[0.0005354086,0.0009368641,0.001498835,0.0007091522,0.001461053,0.001975652,0.003052718,0.003747005,0.01390031],"category_scores_gemma":[0.003622711,0.0007836042,0.001272502,0.001163929,0.001759801,0.003195905,0.002856891,0.002576754,0.001517911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001435694,"about_ca_system_score_gemma":0.001003497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01210507,"about_ca_topic_score_gemma":0.006921315,"domain_scores_codex":[0.9994965,0.0001674542,0.00001903941,0.00008744189,0.00008057499,0.0001490065],"domain_scores_gemma":[0.9988446,0.0005892331,0.0001368961,0.00008627708,0.0001006989,0.0002421476],"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":[0.0001861431,0.00005118361,0.0002775795,0.0001168083,0.00003189859,0.0004457122,0.000219474,0.5756178,0.0007429065,0.4100154,0.006958027,0.005337029],"study_design_scores_gemma":[0.00007139523,0.00004450403,0.00008961145,0.00001815638,0.00001526889,0.0001025803,0.0001475199,0.8577788,0.0001520657,0.1371739,0.004385686,0.00002050631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1517323,0.001598323,0.659411,0.006893243,0.001122713,0.0002746508,0.001232751,0.00035533,0.1773797],"genre_scores_gemma":[0.8180491,0.001611541,0.04561174,0.0008114397,0.0003673023,0.0003563897,0.0006172652,0.0002439008,0.1323314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01390031,"threshold_uncertainty_score":0.04650116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05684704296843068,"score_gpt":0.2945540914198583,"score_spread":0.2377070484514276,"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."}}