{"id":"W2115303412","doi":"10.1109/isita.2008.4895457","title":"Simple and efficient solution of the identifiability problem for hidden Markov sources and quantum random walks","year":2008,"lang":"en","type":"article","venue":"","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Pacific Institute for the Mathematical Sciences","funders":"","keywords":"Identifiability; Hidden Markov model; Markov chain; Simple (philosophy); Random walk; Markov process; Computer science; Mathematics; Ergodicity; Variable-order Markov model; Algorithm; Markov model; Theoretical computer science; Discrete mathematics; Artificial intelligence; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002101524,0.001236039,0.001407772,0.00103973,0.0009784395,0.00142281,0.001813096,0.002151299,0.007393888],"category_scores_gemma":[0.009498998,0.000807674,0.001547529,0.0008676523,0.001504176,0.002992315,0.003346657,0.003534383,0.001593468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006835701,"about_ca_system_score_gemma":0.002057416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008310684,"about_ca_topic_score_gemma":0.0009267869,"domain_scores_codex":[0.9989012,0.0003325402,0.00009016559,0.0002481433,0.0003319186,0.00009606127],"domain_scores_gemma":[0.9955559,0.003383307,0.0002530801,0.000399102,0.0003074079,0.0001012133],"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":[0.00008930301,0.0001356759,0.0004898876,0.0003423987,0.00009125422,0.000355181,0.0002803661,0.2220869,0.006470493,0.6094388,0.00454556,0.1556742],"study_design_scores_gemma":[0.00003081327,0.00002936391,0.00006867456,0.00002031631,0.00001341234,0.0001204514,0.00003665347,0.6538191,0.001312862,0.3417736,0.002750276,0.00002433474],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001206113,0.00003471262,0.9979132,0.00008463751,0.00001951231,0.00003294812,0.00003143159,0.0001022872,0.0005751633],"genre_scores_gemma":[0.06752645,0.0002071344,0.9286383,0.0001065538,0.00008553513,0.0003349473,0.0003510655,0.0001298972,0.002620116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007393888,"threshold_uncertainty_score":0.02473503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01260708402831833,"score_gpt":0.2312989537284225,"score_spread":0.2186918697001042,"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."}}