{"id":"W2138587069","doi":"10.1109/acssc.1993.342339","title":"Recursive parameter estimation for partially observed Markov chains","year":2002,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Markov chain; Markov process; Computer science; Variable-order Markov model; Applied mathematics; Markov model; Mathematics; Continuous-time Markov chain; Algorithm; Mathematical optimization; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002653294,0.00009617384,0.0001052953,0.00006589754,0.00007695105,0.0001672343,0.0003876721,0.0000662177,0.00007100797],"category_scores_gemma":[0.0001694793,0.00008722347,0.00006767594,0.0001732644,0.00001896014,0.0005469266,0.00005600388,0.0000575876,0.00005444177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002402074,"about_ca_system_score_gemma":0.00001261609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000043299,"about_ca_topic_score_gemma":0.000009889142,"domain_scores_codex":[0.9991579,0.00005765654,0.000196764,0.0002599598,0.0001442613,0.0001834704],"domain_scores_gemma":[0.9991711,0.0002045196,0.00007740463,0.0003855371,0.0001041426,0.0000573375],"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":[0.000008449903,0.0001447825,0.00006421054,0.00001412184,0.00002054063,0.000001945759,0.002420726,0.0005469896,0.0002709686,0.7830557,0.04877257,0.164679],"study_design_scores_gemma":[0.0002118196,0.0001425144,0.0002131109,0.000007162132,0.000003421455,0.000002533177,0.000008564671,0.9565498,0.01002779,0.02816615,0.004521574,0.0001456118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002573391,0.00001780128,0.9876774,0.005133912,0.00009779684,0.0004334326,0.000001535602,0.0005403275,0.003524387],"genre_scores_gemma":[0.2393799,0.000006854457,0.7560447,0.001695148,0.00002353153,0.0001339255,0.000004704683,0.000007412787,0.002703776],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9560028,"threshold_uncertainty_score":0.355687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07159037292271393,"score_gpt":0.2780911712373368,"score_spread":0.2065007983146229,"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."}}