{"id":"W2136065708","doi":"","title":"Skip Context Tree Switching","year":2014,"lang":"en","type":"article","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Generalized suffix tree; Computer science; Suffix tree; Suffix; Class (philosophy); Context (archaeology); Tree (set theory); Set (abstract data type); Artificial intelligence; Weighting; Probabilistic logic; Sequence (biology); Regret; Bounded function; Machine learning; Pattern recognition (psychology); Algorithm; Mathematics; Data structure; Combinatorics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001579965,0.00005939491,0.00007153858,0.00002742749,0.00008305369,0.0001220704,0.0005758243,0.00002181768,0.00003481342],"category_scores_gemma":[0.00002108189,0.0000419682,0.00002430515,0.00007250924,0.000005843277,0.000422472,0.000286239,0.00005542159,0.0002115074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005671869,"about_ca_system_score_gemma":0.000008797004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007394361,"about_ca_topic_score_gemma":0.00002033084,"domain_scores_codex":[0.9994359,0.00002503923,0.00008888918,0.0001943207,0.0001254848,0.0001303519],"domain_scores_gemma":[0.9993861,0.00006188561,0.00002542505,0.0004464479,0.00001934252,0.00006078939],"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":[4.640794e-7,0.00001029726,0.00008422377,9.895339e-7,0.000001266862,8.64202e-7,0.0000714074,0.00000303037,0.0003928166,0.1928634,0.004817689,0.8017536],"study_design_scores_gemma":[0.0003452061,0.00005867246,0.003022763,0.00001548284,0.000001309516,0.000009403732,0.00002011253,0.7705193,0.002269108,0.01412212,0.2094421,0.0001744332],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00218999,0.00002317191,0.9596028,0.0005598449,0.0002409109,0.00002783404,1.880642e-7,0.000155462,0.0371998],"genre_scores_gemma":[0.8906427,0.000001848235,0.1072258,0.001175628,0.00009283359,0.000001925668,0.000001002646,0.000003171577,0.0008550173],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8884528,"threshold_uncertainty_score":0.2718571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009160082819927709,"score_gpt":0.2174409041242683,"score_spread":0.2082808213043406,"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."}}