{"id":"W3158797200","doi":"10.4230/lipics.mfcs.2021.57","title":"Online Domination: The Value of Getting to Know All Your Neighbors","year":2021,"lang":"en","type":"preprint","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Bipartite graph; Combinatorics; Competitive analysis; Vertex (graph theory); Mathematics; Graph; Planar graph; Node (physics); Set (abstract data type); Computer science; Discrete mathematics; Upper and lower bounds","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"],"consensus_categories":[],"category_scores_codex":[0.001430361,0.0005207799,0.0006995797,0.0003978493,0.0002928878,0.001057925,0.003313506,0.0003906962,0.00004004142],"category_scores_gemma":[0.0004197567,0.0004131869,0.0004485091,0.0005937325,0.0001078272,0.001012292,0.004098127,0.001060191,0.00003211095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001802902,"about_ca_system_score_gemma":0.0004343298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004102914,"about_ca_topic_score_gemma":0.00003420395,"domain_scores_codex":[0.9957911,0.0001497076,0.001791517,0.0004940481,0.001017645,0.0007559851],"domain_scores_gemma":[0.9954323,0.0002868827,0.0009659096,0.001787639,0.00124252,0.0002848036],"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":[0.0001701749,0.0032077,0.002184329,0.008010995,0.001826354,0.00003155711,0.2382183,0.4492483,0.0002234042,0.1324775,0.03271097,0.1316904],"study_design_scores_gemma":[0.001444249,0.000183016,0.000484471,0.0008054082,0.00005691511,0.00002796906,0.00249698,0.9345587,0.0007470672,0.0009832921,0.05748289,0.000729053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0285636,0.0001661804,0.9548444,0.007870416,0.002044115,0.002737053,0.0006125761,0.0002161863,0.002945475],"genre_scores_gemma":[0.251627,0.0004359969,0.7327586,0.009652657,0.0005841535,0.0004819798,0.003042098,0.0001280042,0.001289511],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4853103,"threshold_uncertainty_score":0.9999791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03033192069342238,"score_gpt":0.3110980857950028,"score_spread":0.2807661651015804,"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."}}