{"id":"W2952754000","doi":"10.7155/jgaa.00421","title":"Lower Bounds for Graph Exploration Using Local Policies","year":2017,"lang":"en","type":"preprint","venue":"Journal of Graph Algorithms and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bounded function; Graph; Computer science; Abstraction; Exponential function; Theoretical computer science; Enhanced Data Rates for GSM Evolution; Robot; Combinatorics; Mathematics; Discrete mathematics; Mathematical optimization; 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":[0.006978052,0.00438269,0.003340694,0.003013531,0.002225152,0.007212249,0.007059452,0.003563166,0.02301669],"category_scores_gemma":[0.0517272,0.001447321,0.003526989,0.003807418,0.004074841,0.01576898,0.007190925,0.01114432,0.004620957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005323283,"about_ca_system_score_gemma":0.004038329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002117627,"about_ca_topic_score_gemma":0.003667116,"domain_scores_codex":[0.9916283,0.002161386,0.0003318931,0.001458377,0.00197316,0.002446802],"domain_scores_gemma":[0.9373668,0.04946034,0.0026504,0.005410994,0.002126956,0.002984542],"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":[0.0009308908,0.0005445256,0.003369151,0.001607958,0.0002482874,0.0002685145,0.0007336831,0.4906038,0.005535916,0.3858626,0.02001287,0.09028184],"study_design_scores_gemma":[0.0000669436,0.0001752385,0.0004233695,0.0002242404,0.0001247612,0.0002118244,0.0001362409,0.7151151,0.00222585,0.2758115,0.005431301,0.00005375121],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03013957,0.00668089,0.9012277,0.004225761,0.0003809589,0.0003191472,0.001156413,0.002392384,0.05347724],"genre_scores_gemma":[0.6563401,0.007266785,0.3034289,0.002036477,0.0009685309,0.001617159,0.00240825,0.003595168,0.02233848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02301669,"threshold_uncertainty_score":0.07699853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06704610915214952,"score_gpt":0.3427686469278052,"score_spread":0.2757225377756556,"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."}}