{"id":"W2072372110","doi":"10.1007/s11222-011-9248-x","title":"On-line changepoint detection and parameter estimation with application to genomic data","year":2011,"lang":"en","type":"article","venue":"Statistics and Computing","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Centre National de la Recherche Scientifique; Pacific Institute for the Mathematical Sciences","keywords":"Computer science; Algorithm; Partition (number theory); Bayesian probability; Particle filter; Context (archaeology); Expectation–maximization algorithm; Data mining; Maximum likelihood; Mathematics; Artificial intelligence; Kalman filter; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00007899643,0.00006390826,0.00004892151,0.00002599856,0.00007071547,0.00001833811,0.00005596368,0.00002722111,0.000001556891],"category_scores_gemma":[0.00002601437,0.00005558553,0.000002842283,0.00003373528,0.00001908509,0.000002186215,0.00008595331,0.00002945781,0.000001712268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004429355,"about_ca_system_score_gemma":0.000009103695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001886636,"about_ca_topic_score_gemma":0.00002620274,"domain_scores_codex":[0.9995265,0.00001363652,0.00008380192,0.0002601137,0.00004451176,0.00007142538],"domain_scores_gemma":[0.9996402,0.0000105158,0.00005361922,0.0002192601,0.00002979432,0.00004656322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001593384,0.00003409247,0.0003405124,0.00002597442,0.00001839481,5.645111e-7,0.0002643147,0.0004519,0.1331069,0.001507082,0.000243416,0.8638476],"study_design_scores_gemma":[0.0007468711,0.001482577,0.03878734,0.00004591908,0.00004296242,0.00002575183,0.0001708855,0.897153,0.05545569,0.00353052,0.002176559,0.0003819108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2460425,0.00003044611,0.7536977,0.00001981202,0.00002390948,0.0001061525,0.00002230407,0.000005149603,0.00005200091],"genre_scores_gemma":[0.9203097,0.00001708646,0.07933965,0.0001505667,0.00003900659,0.000008137475,0.0001142565,0.000007780069,0.0000138283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8967011,"threshold_uncertainty_score":0.2266712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0381693865443931,"score_gpt":0.2856644862224921,"score_spread":0.247495099678099,"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."}}