{"id":"W2235204424","doi":"10.48550/arxiv.1111.3182","title":"Context Tree Switching","year":2011,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Weighting; Tree (set theory); Context (archaeology); Markov chain; Computer science; Binary tree; Generalization; Mathematics; Class (philosophy); Markov process; Algorithm; Artificial intelligence; Machine learning; Statistics; Combinatorics; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001107922,0.00009310469,0.0001001312,0.0001168387,0.0001055943,0.00003148671,0.0006520379,0.00004707097,0.0002751838],"category_scores_gemma":[0.00002289458,0.0000985433,0.00008308919,0.0003457521,0.00002763337,0.0005123304,0.0001248895,0.00008228697,0.0006973025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003111953,"about_ca_system_score_gemma":0.00002542791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009088854,"about_ca_topic_score_gemma":0.00007970045,"domain_scores_codex":[0.9993122,0.00005061257,0.00007766974,0.0003350512,0.00003913055,0.0001853577],"domain_scores_gemma":[0.9993535,0.00005541351,0.00005128094,0.0003787771,0.00004974066,0.0001113106],"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":[0.00002519499,0.00013777,0.005234162,0.000005274007,0.00004582458,0.0005295615,0.001068845,0.00001155813,0.0003517795,0.7938065,0.0004514983,0.198332],"study_design_scores_gemma":[0.00443058,0.0004866917,0.06145737,0.0001387936,0.0001528829,0.0001565639,0.003417226,0.5394596,0.05048217,0.3203368,0.01702488,0.002456482],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2595191,0.00000955496,0.6404207,0.0000418129,0.0001718185,0.00005708403,6.308503e-7,0.0002222546,0.09955706],"genre_scores_gemma":[0.9938813,0.00001239322,0.004445589,0.0002799589,0.00001584075,1.635036e-7,2.627652e-7,0.000005011105,0.001359502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7343621,"threshold_uncertainty_score":0.8962645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1424956576611086,"score_gpt":0.1649113809662521,"score_spread":0.02241572330514352,"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."}}