{"id":"W2811181433","doi":"10.4230/lipics.concur.2018.33","title":"Automatic Analysis of Expected Termination Time for Population Protocols","year":2018,"lang":"en","type":"preprint","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Grantová Agentura České Republiky; Alexander von Humboldt-Stiftung","keywords":"Computation; Computer science; Protocol (science); Population; Parametric statistics; Upper and lower bounds; Function (biology); Distributed computing; Algorithm; Theoretical computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01121398,0.001382572,0.001535482,0.00208395,0.001355193,0.003328593,0.00375304,0.00226814,0.003961354],"category_scores_gemma":[0.0969535,0.0009643643,0.001543092,0.001165151,0.004830556,0.00555782,0.003177349,0.004994791,0.0006222172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003874973,"about_ca_system_score_gemma":0.002917582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001143565,"about_ca_topic_score_gemma":0.0007395483,"domain_scores_codex":[0.9903976,0.003455071,0.0005335596,0.001671885,0.002813031,0.001128989],"domain_scores_gemma":[0.859639,0.1181652,0.006642179,0.007234468,0.006410154,0.001909164],"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":[0.0007995296,0.0002048578,0.005724698,0.0003008345,0.0001347668,0.0002979667,0.0009190681,0.7283048,0.01512898,0.2114292,0.002221107,0.03453425],"study_design_scores_gemma":[0.00003606528,0.00004327252,0.0001960332,0.00001306247,0.00001425154,0.00003651328,0.00002185028,0.9394023,0.002395569,0.05756794,0.0002589118,0.00001416434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0827189,0.0001815779,0.9123993,0.0005247146,0.00003793527,0.0001162444,0.0001472485,0.001222373,0.002651671],"genre_scores_gemma":[0.8205238,0.0001732796,0.1752526,0.0001711661,0.00009958169,0.0006615423,0.0005080553,0.0006760018,0.001933909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01121398,"threshold_uncertainty_score":0.05930585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829018276171908,"score_gpt":0.3099208662115419,"score_spread":0.2916306834498228,"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."}}