{"id":"W2399456157","doi":"","title":"Computing Derivatives via Compression: An Exact Scheme.","year":2011,"lang":"en","type":"article","venue":"Cologne Twente Workshop on Graphs and Combinatorial Optimization","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Scheme (mathematics); Computer science; Compression (physics); Data compression; Computational science; Parallel computing; Algorithm; Mathematics; Materials science","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":[0.0005095691,0.0003761473,0.0004265643,0.0002570535,0.0005374802,0.0002435989,0.0008932159,0.000229567,0.00005470009],"category_scores_gemma":[0.00009553524,0.0003544259,0.0001001857,0.0009471363,0.0002143279,0.0007595091,0.0005935073,0.0003501607,0.000004614467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005790539,"about_ca_system_score_gemma":0.00004945347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001774212,"about_ca_topic_score_gemma":0.000002170982,"domain_scores_codex":[0.997371,0.0003719495,0.0004874486,0.0009290663,0.0003774741,0.0004630599],"domain_scores_gemma":[0.9981378,0.0002839437,0.0002978244,0.0007240046,0.0002847314,0.0002716684],"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":[0.0006589633,0.005223076,0.01287757,0.00007767079,0.0002035409,0.00007833845,0.007076716,0.06059831,0.0003946297,0.7490392,0.0007044901,0.1630674],"study_design_scores_gemma":[0.001828072,0.001031662,0.007785321,0.00007982138,0.00001764348,0.00001334262,0.0001183865,0.9420012,0.0003370098,0.04607721,0.0001495048,0.0005608577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0961258,0.0001728075,0.8964904,0.0001675106,0.004467517,0.0005825065,0.000001474445,0.0005886187,0.001403367],"genre_scores_gemma":[0.8414016,0.00006374065,0.1581299,0.0002130635,0.0001112247,0.00002085964,0.00001849677,0.00002382465,0.00001733024],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8814029,"threshold_uncertainty_score":0.9998907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02798756685452442,"score_gpt":0.2556320087688388,"score_spread":0.2276444419143144,"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."}}