{"id":"W4251527353","doi":"10.1007/978-94-017-1506-5_1","title":"Random Media","year":2003,"lang":"en","type":"book-chapter","venue":"Mathematical modelling: theory and applications","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Markov chain; Ergodic theory; Martingale (probability theory); Markov property; Mathematics; Markov renewal process; Markov process; Statistical physics; Variable-order Markov model; Computer science; Discrete mathematics; Pure mathematics; Markov model; Applied mathematics; Statistics; Physics","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":[0.0002958166,0.0007485885,0.0006367475,0.001645888,0.0007262951,0.002861949,0.00073702,0.001036456,0.06169801],"category_scores_gemma":[0.001904559,0.000322589,0.0003474077,0.001165816,0.0009716956,0.002773015,0.001115938,0.001234664,0.02423389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005376731,"about_ca_system_score_gemma":0.0004273034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005674576,"about_ca_topic_score_gemma":0.0005780306,"domain_scores_codex":[0.9996731,0.00004981022,0.00001341705,0.00008816405,0.0001498882,0.00002550655],"domain_scores_gemma":[0.9994617,0.0001819548,0.00003833504,0.0001404518,0.0001316577,0.00004589863],"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":[0.00003066969,0.00002475608,0.0001156217,0.0001727242,0.00001660669,0.0001289838,0.00008885467,0.001760555,0.00282915,0.7829309,0.1051377,0.1067635],"study_design_scores_gemma":[0.00001284592,0.00002402076,0.0002603068,0.00008296989,0.00001956935,0.0004183756,0.00007054974,0.009538203,0.003138919,0.4159915,0.570413,0.00002965062],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004771743,0.009865425,0.1696555,0.00476581,0.003999342,0.00009822831,0.001079782,0.002138781,0.8036253],"genre_scores_gemma":[0.08251563,0.008607543,0.02886586,0.001565484,0.002601098,0.0001912995,0.001289698,0.0007008191,0.8736625],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06169801,"threshold_uncertainty_score":0.2064005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02993747984002548,"score_gpt":0.2327226450670196,"score_spread":0.2027851652269941,"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."}}