{"id":"W4411019622","doi":"10.1109/tcss.2025.3566055","title":"A Dual-Level Bio-Inspired Optimization Algorithm for Cloud Manufacturing Service Evaluation on Industrial Internet of Things (IIoT) Platforms","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Social Systems","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Cloud computing; Industrial Internet; Internet of Things; Computer science; Dual (grammatical number); Service (business); The Internet; Distributed computing; Artificial intelligence; Algorithm; Computer security; World Wide Web; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003591721,0.0002365161,0.0002882275,0.0003512106,0.0002079179,0.0001139609,0.0001425112,0.0003354284,0.00002617364],"category_scores_gemma":[0.000006292209,0.0002617478,0.000138301,0.0004112035,0.00003215364,0.0004864428,0.000001369318,0.0002813373,0.00001145292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005073101,"about_ca_system_score_gemma":0.0001272627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007429112,"about_ca_topic_score_gemma":0.000004794968,"domain_scores_codex":[0.9982538,0.00003689614,0.0007063452,0.0002175969,0.0005768252,0.0002084856],"domain_scores_gemma":[0.9991162,0.0002695354,0.0001400068,0.00009507922,0.0003300407,0.000049162],"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":[0.00005057893,0.00007640542,7.616992e-7,0.0001453534,0.0001982583,1.712719e-7,0.0006473638,0.9414551,0.00001191645,0.000680499,0.0005148912,0.05621874],"study_design_scores_gemma":[0.001918028,0.00006668366,0.00002734542,0.0002706521,0.00007566539,0.000002083784,0.000407209,0.992599,0.003654113,0.0005230646,0.000240128,0.0002160454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01294517,0.000008500822,0.9793834,0.0001077767,0.003767313,0.001242155,0.0003763545,0.0002421933,0.001927151],"genre_scores_gemma":[0.9946468,0.000001601051,0.004253055,0.00008523963,0.0002555841,0.0003311133,0.0002396446,0.0000385567,0.0001484187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9817016,"threshold_uncertainty_score":0.9999835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05419158661573991,"score_gpt":0.2717518372074251,"score_spread":0.2175602505916852,"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."}}