{"id":"W2950969151","doi":"10.48550/arxiv.1301.7119","title":"How to Meet Asynchronously at Polynomial Cost","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Polynomial; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001855971,0.0003178914,0.0003128017,0.0003356333,0.000233954,0.0005884652,0.002364679,0.0002738036,0.0001448218],"category_scores_gemma":[0.00004256939,0.0003612589,0.0001667717,0.0005377456,0.00008362511,0.0005615243,0.004832028,0.0003059052,0.0005987683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005824909,"about_ca_system_score_gemma":0.0002548781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000180717,"about_ca_topic_score_gemma":0.0001913465,"domain_scores_codex":[0.9978265,0.0001519005,0.0001541381,0.001195895,0.0001430849,0.0005284469],"domain_scores_gemma":[0.9976721,0.0000655764,0.0001569284,0.001352194,0.0002424899,0.0005106903],"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":[0.0000391519,0.0001496335,0.001217333,0.00008050507,0.0001289394,0.0002246154,0.0007662786,0.7413561,0.00015322,0.1766459,0.07639531,0.002842992],"study_design_scores_gemma":[0.0007774947,0.0001229098,0.0003885762,0.0000667824,0.00002497124,0.00000659895,0.00004884626,0.9522053,0.0002546603,0.004066508,0.04117339,0.0008639931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0377634,0.00002115709,0.9489424,0.002419157,0.0007972158,0.001042076,0.00002209454,0.0003535196,0.008638976],"genre_scores_gemma":[0.9579302,0.00006295813,0.01055194,0.0005265795,0.0001196747,0.000006012508,0.00001879672,0.00002469399,0.03075911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9383904,"threshold_uncertainty_score":0.9998839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07055463355348017,"score_gpt":0.1898684458491258,"score_spread":0.1193138122956456,"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."}}