{"id":"W2582003296","doi":"10.1103/physreve.95.062144","title":"When memory pays: Discord in hidden Markov models","year":2017,"lang":"en","type":"article","venue":"Physical review. E","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hidden Markov model; Ising model; Markov chain; Markov model; Hidden semi-Markov model; Computer science; Variable-order Markov model; Statistical physics; State (computer science); Markov process; Artificial intelligence; Algorithm; Mathematics; Machine learning; Statistics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005291346,0.000328925,0.0009983957,0.0008766576,0.001138396,0.003061456,0.00178906,0.002447721,0.003557423],"category_scores_gemma":[0.04728793,0.0005535597,0.0005319669,0.0005960654,0.003903433,0.008707136,0.001979743,0.002694055,0.0002609121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001991557,"about_ca_system_score_gemma":0.000862808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002090961,"about_ca_topic_score_gemma":0.001757981,"domain_scores_codex":[0.9987195,0.0005833375,0.00008680251,0.0001923071,0.0001945344,0.0002236397],"domain_scores_gemma":[0.9690865,0.02541894,0.002246941,0.001723391,0.0007783212,0.0007458634],"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":[0.0003815569,0.00007213829,0.005980862,0.000241395,0.00009648844,0.0009154804,0.001385248,0.05106603,0.001596922,0.9002432,0.003542651,0.03447805],"study_design_scores_gemma":[0.00002204845,0.00003922356,0.001189335,0.00007192918,0.00002601562,0.0001025737,0.0001751549,0.1035447,0.0007847137,0.8931522,0.0008583939,0.00003377734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6844398,0.009125676,0.2526951,0.02617062,0.0006566474,0.00006342964,0.0002903405,0.0005443416,0.02601407],"genre_scores_gemma":[0.992494,0.0009910632,0.004390456,0.0004329069,0.0001794852,0.00002257202,0.0000367901,0.00005596098,0.001396848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005291346,"threshold_uncertainty_score":0.02798361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06033979071210724,"score_gpt":0.336048576599652,"score_spread":0.2757087858875448,"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."}}