{"id":"W2107791851","doi":"","title":"An Exact A* Method for Deciphering Letter-Substitution Ciphers","year":2010,"lang":"en","type":"article","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Generalization; Encoding (memory); Relation (database); Decipherment; Theoretical computer science; Set (abstract data type); ENCODE; Substitution (logic); Algorithm; Artificial intelligence; Programming language; Data mining; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003559888,0.0000927711,0.00008795601,0.00003371263,0.000162187,0.0001999824,0.0006972593,0.00005949205,0.00005117725],"category_scores_gemma":[0.0000240766,0.00007362241,0.00004112273,0.0001027858,0.00001615708,0.001134587,0.0001145415,0.0001096182,0.00001423465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000986803,"about_ca_system_score_gemma":0.00002641228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006689233,"about_ca_topic_score_gemma":0.00003799575,"domain_scores_codex":[0.9991869,0.00002320911,0.0001226601,0.0003351046,0.0001301593,0.0002019279],"domain_scores_gemma":[0.9991049,0.00007921561,0.00003994047,0.0006282714,0.00004480491,0.0001028548],"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":[0.000008228443,0.00007288691,0.0001043205,0.000007676213,0.000007794933,0.000003929775,0.0001328457,0.0004077899,0.2441155,0.1787755,0.003930228,0.5724334],"study_design_scores_gemma":[0.0002770865,0.00006024066,0.0007967224,0.000004910365,0.000003086055,0.00001034158,0.000007933705,0.8643796,0.02466401,0.002907715,0.1067124,0.0001759225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009518271,0.000004974417,0.9878426,0.0002868171,0.0009363381,0.0001342644,0.000002471452,0.0002122328,0.001062037],"genre_scores_gemma":[0.08078596,7.056083e-7,0.9182768,0.0005764259,0.0002537623,0.00001991734,0.000007459446,0.000006002349,0.0000730024],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8639718,"threshold_uncertainty_score":0.3002235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843912016128971,"score_gpt":0.3156345772994884,"score_spread":0.2971954571381986,"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."}}