{"id":"W1517540866","doi":"10.1002/rsa.20693","title":"The cutoff phenomenon for random birth and death chains","year":2016,"lang":"en","type":"preprint","venue":"Random Structures and Algorithms","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Statistics Canada","funders":"","keywords":"Cutoff; Pi; Tridiagonal matrix; Mathematics; Combinatorics; Block (permutation group theory); Random matrix; Distribution (mathematics); Stationary distribution; Markov chain; Matrix (chemical analysis); Physics; Mathematical analysis; Quantum mechanics; Statistics; Chemistry; Eigenvalues and eigenvectors; Geometry","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":[0.003709143,0.0004581598,0.0009229598,0.00148019,0.001215893,0.001955248,0.001315512,0.001415033,0.002929726],"category_scores_gemma":[0.02545727,0.0004149549,0.0007456555,0.000823702,0.003577536,0.002841896,0.001696318,0.002256388,0.0003066056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002097708,"about_ca_system_score_gemma":0.0009624807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002232927,"about_ca_topic_score_gemma":0.001649544,"domain_scores_codex":[0.9988784,0.0004919326,0.0000500233,0.0002034455,0.0001948439,0.0001813448],"domain_scores_gemma":[0.9865095,0.009307499,0.0013901,0.001034828,0.0007683525,0.0009897453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001331761,0.0000739372,0.005016111,0.0000840872,0.0000400186,0.0004965038,0.0005681959,0.0511907,0.002379635,0.932687,0.001427016,0.005903533],"study_design_scores_gemma":[0.00004861104,0.00003391604,0.001125024,0.00005405511,0.00001510291,0.000162648,0.0001298768,0.4264719,0.0008158938,0.5700942,0.001024566,0.00002425038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.47796,0.0009558455,0.5073457,0.001342794,0.00006537649,0.0001003483,0.0002136197,0.0003932305,0.01162318],"genre_scores_gemma":[0.9659274,0.0003735568,0.02983914,0.0001956882,0.00005719192,0.0001764059,0.0001664407,0.00007905155,0.003185053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003709143,"threshold_uncertainty_score":0.01961601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04574825245586694,"score_gpt":0.3382156847691768,"score_spread":0.2924674323133099,"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."}}