{"id":"W3197727390","doi":"10.2139/ssrn.3314856","title":"An Approximation Method of Parallel Processing System with Big Data","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Assumption University","funders":"","keywords":"Computer science; Big data; Parallel computing; Data mining","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":[0.0008245458,0.0006395601,0.0008403775,0.000840923,0.000851203,0.00105312,0.001557276,0.000588293,0.00389009],"category_scores_gemma":[0.002669744,0.000354816,0.0008338308,0.001269741,0.0005907281,0.001518611,0.001116539,0.001345488,0.0007067733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009021243,"about_ca_system_score_gemma":0.001690238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006221389,"about_ca_topic_score_gemma":0.004285149,"domain_scores_codex":[0.9992506,0.0001902912,0.00004701086,0.0001426249,0.0002857762,0.00008361687],"domain_scores_gemma":[0.9991789,0.0002728241,0.00003855816,0.000155092,0.0002919609,0.00006253905],"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":[0.0006975052,0.0001648801,0.002653646,0.0004018728,0.0001605052,0.0002919293,0.0002655583,0.4840986,0.01051912,0.114024,0.01641081,0.3703115],"study_design_scores_gemma":[0.00001756944,0.0000232609,0.00008400805,0.000005254976,0.00001376937,0.00004063422,0.00001109884,0.9877532,0.0007090665,0.009555214,0.001781937,0.00000508592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006053922,0.0003551393,0.9909508,0.000172826,0.0001898008,0.00003313772,0.00003944414,0.0004439638,0.001760885],"genre_scores_gemma":[0.2644948,0.0008764099,0.725054,0.0002017316,0.0003389496,0.000260598,0.0002974782,0.0002506909,0.008225328],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006221389,"threshold_uncertainty_score":0.01301366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02697878274162958,"score_gpt":0.292842205595772,"score_spread":0.2658634228541424,"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."}}