{"id":"W2163928079","doi":"10.1109/ipps.1999.760426","title":"The characterization of data-accumulating algorithms","year":2003,"lang":"en","type":"article","venue":"","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Speedup; Computer science; Algorithm; Parallelism (grammar); Computation; Class (philosophy); Geodetic datum; Parallel algorithm; Parallel computing; Characterization (materials science); Unitary state; Artificial intelligence","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":[0.0002088438,0.00005321714,0.00005925301,0.0000179194,0.00006025875,0.00002753576,0.0001399752,0.00002576881,0.00005933004],"category_scores_gemma":[0.00005775854,0.00003816569,0.00001153685,0.0001371043,0.00001359223,0.0001428517,0.00001388833,0.00004287905,0.00001001377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005702593,"about_ca_system_score_gemma":0.000007471234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001314605,"about_ca_topic_score_gemma":7.778581e-7,"domain_scores_codex":[0.9995718,0.00001607269,0.0001653047,0.00007318251,0.00008278123,0.00009082887],"domain_scores_gemma":[0.999579,0.00005032985,0.00002492158,0.0002909577,0.00003428561,0.00002052545],"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":[0.000007706361,0.00007435648,0.001895188,0.0001037767,0.0002678353,0.000002469262,0.0008668202,0.4319688,0.05925035,0.02563544,0.0005280125,0.4793992],"study_design_scores_gemma":[0.00008469223,0.000003056148,0.0002483893,0.000003695945,0.000004488861,0.000001369459,0.00005529643,0.986688,0.008942719,0.0000279161,0.003881699,0.00005866431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02359242,0.00009126592,0.9669095,0.00003540338,0.0004760441,0.00008996822,0.00001358514,0.0002351522,0.00855661],"genre_scores_gemma":[0.591141,0.0001935833,0.4074432,0.000046183,0.000103764,0.00000730416,0.0001879853,0.0000443403,0.0008326201],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5675486,"threshold_uncertainty_score":0.1556351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04020316304903815,"score_gpt":0.2698056974153192,"score_spread":0.229602534366281,"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."}}