{"id":"W4413977927","doi":"10.1109/tnsm.2025.3606343","title":"Extending WebAssembly for Deep-Learning Inference Across the Cloud Continuum","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières","funders":"","keywords":"Computer science; Cloud computing; Inference; Deep learning; Artificial intelligence; Computer security; 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":[0.001403096,0.001946221,0.001033086,0.0009794366,0.0008859923,0.002229515,0.004894334,0.001257864,0.01077033],"category_scores_gemma":[0.004184624,0.001151289,0.0017146,0.0009864597,0.001195792,0.00454246,0.004335915,0.003243693,0.009766705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001593833,"about_ca_system_score_gemma":0.002848178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0113984,"about_ca_topic_score_gemma":0.01772602,"domain_scores_codex":[0.9984539,0.0001729616,0.0001078802,0.0003973717,0.0006267018,0.0002412941],"domain_scores_gemma":[0.9981877,0.0003131119,0.00008334492,0.0007615208,0.0004719286,0.0001823595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001811459,0.001010181,0.009088261,0.0009369428,0.0004083174,0.001294991,0.0006122008,0.08285824,0.03589706,0.04281858,0.1620433,0.6612205],"study_design_scores_gemma":[0.0001492872,0.0001398468,0.001580948,0.000100662,0.000059043,0.0003702939,0.000106259,0.835902,0.05201295,0.02410286,0.08535818,0.0001176939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01561597,0.0008932669,0.7704061,0.0005130261,0.0003347942,0.0002268787,0.000891444,0.2000146,0.0111039],"genre_scores_gemma":[0.2410258,0.0008988169,0.6966765,0.002018277,0.0001606992,0.0004436018,0.009319444,0.02753172,0.02192523],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0113984,"threshold_uncertainty_score":0.03603029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05248531674182655,"score_gpt":0.3690033185938535,"score_spread":0.316518001852027,"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."}}