{"id":"W3016074430","doi":"10.1023/b:mone.0000031585.26814.2d","title":"A Parallel Hill Climbing Algorithm for Pushing Dependent Data in Clients–Providers–Servers Systems","year":2004,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Consejo Nacional de Ciencia y Tecnología","keywords":"Computer science; Random access; Server; Access time; Algorithm; Computer network; Permutation (music); Hill climbing; Operating system","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":[0.0005855162,0.0001398692,0.0002077267,0.00004451113,0.0002395874,0.0003895872,0.0008962105,0.00009149699,3.366247e-7],"category_scores_gemma":[0.000005848171,0.0001369649,0.00003391378,0.0003039307,0.00002831,0.0005167038,0.0002999264,0.0001394242,0.000003212395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006794027,"about_ca_system_score_gemma":0.00003998068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00040348,"about_ca_topic_score_gemma":0.0001356309,"domain_scores_codex":[0.9984354,0.00003141442,0.0003941956,0.0006465415,0.000144586,0.0003478007],"domain_scores_gemma":[0.9987031,0.00008873767,0.0001400202,0.0009070903,0.00004942379,0.0001116853],"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":[0.000002781454,0.0001729173,0.000310126,0.00004773135,0.00001898079,0.000003550301,0.00008745576,0.7634797,0.000009463042,0.04159056,0.0004420077,0.1938348],"study_design_scores_gemma":[0.0009031817,0.00002988498,0.0002165304,0.00008055045,0.000007040184,0.00001139352,0.0002094895,0.953023,0.000001412262,0.0005290576,0.04480292,0.0001856041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006390713,0.002157657,0.9948345,0.0001488838,0.0001856278,0.001764231,0.00009771549,0.00008155063,0.00009077758],"genre_scores_gemma":[0.9770378,0.0002887466,0.01763661,0.0001584392,0.0003088287,0.004181871,0.0003115033,0.00001883414,0.00005730715],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9771979,"threshold_uncertainty_score":0.5585265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01970672827753642,"score_gpt":0.2657152183151447,"score_spread":0.2460084900376083,"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."}}