{"id":"W4392452252","doi":"10.1007/978-3-031-55598-5_10","title":"Space-Efficient Conversions from SLPs","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Space (punctuation); Programming language; Theoretical computer science; Operating system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004482315,0.0005773475,0.0005083534,0.0007692083,0.0003075839,0.0009362162,0.004046029,0.0003449807,0.0001104738],"category_scores_gemma":[0.00004116263,0.0004792269,0.0001756465,0.0006455732,0.0005687845,0.0004228489,0.004355286,0.001058465,0.0006646479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003097272,"about_ca_system_score_gemma":0.0005026775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00010759,"about_ca_topic_score_gemma":0.00002181407,"domain_scores_codex":[0.9954728,0.00002128682,0.0004561204,0.002149069,0.001239046,0.0006616465],"domain_scores_gemma":[0.9968229,0.0005038941,0.0001827701,0.002050729,0.0001598542,0.000279856],"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":[0.00001080296,0.00009708593,0.00001732891,0.00006737449,0.0000486104,0.0009317888,0.002037954,0.07087524,0.0004877201,0.2721463,0.001307603,0.6519722],"study_design_scores_gemma":[0.0001592911,0.0000683372,0.00002516658,0.0006029544,0.00001195494,0.00002732317,2.313865e-7,0.8301667,0.000703442,0.1452303,0.02243854,0.0005657439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00006058659,0.001530199,0.9825153,0.001435332,0.00591613,0.000298534,0.00006877928,0.0003252382,0.007849926],"genre_scores_gemma":[0.0661059,0.000184759,0.9253058,0.002198571,0.001997857,0.00001647119,0.00007577535,0.0001065844,0.004008282],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7592915,"threshold_uncertainty_score":0.9997659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01357403941371442,"score_gpt":0.2356956236222676,"score_spread":0.2221215842085532,"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."}}