{"id":"W3014491141","doi":"10.1155/2020/3298460","title":"A Grasshopper Optimization-Based Approach for Task Assignment in Cloud Logistics","year":2020,"lang":"en","type":"article","venue":"Mathematical Problems in Engineering","topic":"Collaboration in agile enterprises","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Ministry of Education of the People's Republic of China","keywords":"Task (project management); Computer science; Matching (statistics); Cloud computing; Genetic algorithm; Service (business); Mathematical optimization; Stability (learning theory); Mode (computer interface); Commodity; Operations research; Engineering; Mathematics; Systems engineering; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002601579,0.0001618617,0.0002319031,0.0001632258,0.00002414684,0.0001382783,0.0001666669,0.00006394814,0.00005565119],"category_scores_gemma":[0.0007999497,0.000159891,0.00004014843,0.0005894997,0.00001646653,0.0001997698,0.00006286449,0.0001263525,0.00001260926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006951217,"about_ca_system_score_gemma":0.00001495474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003907193,"about_ca_topic_score_gemma":0.000001633392,"domain_scores_codex":[0.9989158,0.000004647906,0.000423197,0.0002367497,0.0001785537,0.0002410387],"domain_scores_gemma":[0.9996005,0.0001361241,0.00007240542,0.0001213109,0.00005096509,0.00001870648],"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":[0.000007487899,0.000114066,0.000488614,0.001422296,0.000004695144,0.000001368769,0.00006155513,0.9902969,0.00007173411,0.007162791,0.000338094,0.00003039861],"study_design_scores_gemma":[0.0006231433,0.00000818544,0.000001844944,0.0001196485,0.000009848976,1.299588e-7,0.00004496571,0.997046,0.00001037105,0.001156437,0.0008000104,0.0001794251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00002664512,0.00001867147,0.9967621,0.000648319,0.00008370725,0.0007880159,0.000003148654,0.0001267255,0.001542683],"genre_scores_gemma":[0.9749449,7.431412e-7,0.02388947,0.0004493721,0.0002411588,0.000394398,0.00003304268,0.00003860527,0.00000833054],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9749182,"threshold_uncertainty_score":0.6520166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02531682570964594,"score_gpt":0.2134092852098554,"score_spread":0.1880924595002094,"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."}}