{"id":"W2141195801","doi":"10.1016/j.tcs.2015.10.038","title":"Order compression schemes","year":2015,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Compression (physics); Mathematics; Data compression; Conjecture; Data compression ratio; Sample (material); Lossless compression; Intersection (aeronautics); Dimension (graph theory); Order (exchange); Algorithm; Image compression; Discrete mathematics; Computer science; Combinatorics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001513499,0.0001563163,0.0001650844,0.0001431894,0.0003130193,0.0005005095,0.002591771,0.00004020698,0.00002852033],"category_scores_gemma":[0.0002038259,0.0001149338,0.00003543358,0.001334056,0.001423351,0.0006336449,0.001531404,0.0002543284,0.0002513385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003686,"about_ca_system_score_gemma":0.0001979237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004671795,"about_ca_topic_score_gemma":8.065637e-8,"domain_scores_codex":[0.9976816,0.0001202164,0.0001879926,0.0006192591,0.0008898435,0.0005011522],"domain_scores_gemma":[0.9982203,0.0001096351,0.00005096317,0.0007800799,0.000337512,0.0005015131],"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":[0.000002629412,0.00003695532,0.00009619573,0.000001836605,0.000001267044,0.000009225915,0.0002779597,0.0004307032,0.0001210681,0.9242896,0.0002635348,0.07446898],"study_design_scores_gemma":[0.0002638643,0.000152647,0.000215119,0.00001789558,0.000001325849,0.00004075527,0.000004413492,0.905928,0.001639584,0.0878627,0.003685189,0.0001885232],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01175876,0.0000380822,0.975738,0.002030397,0.0009388794,0.00007108178,2.577139e-7,0.0003959968,0.009028492],"genre_scores_gemma":[0.620896,6.788473e-7,0.3784452,0.0004754261,0.0001430331,0.000001961137,3.527773e-7,0.000004365531,0.00003298974],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9054973,"threshold_uncertainty_score":0.5244396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01427389291218515,"score_gpt":0.2776037236580798,"score_spread":0.2633298307458947,"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."}}