{"id":"W2418598077","doi":"10.1145/2908557","title":"Write Skew and Zipf Distribution","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Storage","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Zipf's law; Computer science; Skew; Workload; Benchmark (surveying); Block (permutation group theory); Class (philosophy); Variety (cybernetics); Parallel computing; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001184213,0.0003320074,0.0004887044,0.001242472,0.0003956301,0.0009552535,0.0005968499,0.0005368359,0.001336801],"category_scores_gemma":[0.01519608,0.0003391923,0.00017199,0.001061475,0.0006011735,0.002004415,0.000509041,0.0004964991,0.0004528625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008418883,"about_ca_system_score_gemma":0.0005266618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000897059,"about_ca_topic_score_gemma":0.001221309,"domain_scores_codex":[0.9988542,0.0001950293,0.00007229449,0.000256404,0.0004534468,0.0001687333],"domain_scores_gemma":[0.9890612,0.006017739,0.001686691,0.00144266,0.001544949,0.0002468088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001290366,0.0004128706,0.2254471,0.0004720558,0.0001882016,0.002137596,0.001475556,0.4708413,0.1163523,0.05081876,0.006696313,0.1238674],"study_design_scores_gemma":[0.00003352438,0.0002864948,0.05989139,0.00004499979,0.00004169293,0.002048637,0.0005206752,0.8704666,0.02612661,0.03721564,0.003237798,0.00008600462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8744116,0.001155295,0.1160438,0.0004940142,0.0000673391,0.0001119805,0.0009263724,0.001117518,0.005671965],"genre_scores_gemma":[0.9965767,0.0001576414,0.00230797,0.00004227907,0.00003244098,0.00003052511,0.0002064399,0.00006308419,0.000582798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001336801,"threshold_uncertainty_score":0.006262779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01648730979935262,"score_gpt":0.2471854480837103,"score_spread":0.2306981382843577,"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."}}