{"id":"W3018088442","doi":"10.1137/1.9781611976465.75","title":"Dynamic Maintenance of Low-Stretch Probabilistic Tree Embeddings with Applications","year":2021,"lang":"en","type":"preprint","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Probabilistic logic; Tree (set theory); Pruning; Algorithm; Computer science; Binary logarithm; Embedding; Combinatorics; Time complexity; Approximation algorithm; Probabilistic analysis of algorithms; Dynamic problem; Mathematics; Discrete mathematics; Theoretical computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003827364,0.0003805906,0.0006985053,0.00004439652,0.0002112929,0.0002457817,0.0008617806,0.0004401998,0.000002676441],"category_scores_gemma":[0.00002151259,0.0003260522,0.0004100387,0.0001559119,0.0004071922,0.00003867208,0.000949386,0.0006369704,3.574226e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006183952,"about_ca_system_score_gemma":0.0003579377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004694264,"about_ca_topic_score_gemma":0.000008243086,"domain_scores_codex":[0.9980003,0.000008720945,0.0005837426,0.0007244162,0.0003322362,0.0003506184],"domain_scores_gemma":[0.9979957,0.0002934704,0.0005672263,0.0008389614,0.0001995056,0.000105161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002958251,0.0004386552,0.000002027117,0.005005674,0.0005968622,0.000001291558,0.01130392,0.0003199693,0.0008352422,0.877983,0.0004237111,0.1030601],"study_design_scores_gemma":[0.002517965,0.00015285,0.000003626608,0.001635765,0.0003166053,0.00002130626,0.003808408,0.1777831,0.002553274,0.8095703,0.0006008047,0.001035957],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02405314,0.00006678492,0.9687108,0.0001523322,0.0001579028,0.003470228,0.0001650668,0.000166658,0.003057028],"genre_scores_gemma":[0.1236657,0.00001939304,0.8737785,0.00005677556,0.0001254054,0.001910427,0.00007116162,0.00004416914,0.0003284958],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1774631,"threshold_uncertainty_score":0.9999192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03287864480673584,"score_gpt":0.2499828280805961,"score_spread":0.2171041832738603,"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."}}