{"id":"W2054642624","doi":"10.1007/s10470-011-9700-z","title":"How different messaging semantics can affect SCA applications performances: a benchmark comparison","year":2011,"lang":"en","type":"article","venue":"Analog Integrated Circuits and Signal Processing","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Common Object Request Broker Architecture; Computer science; Middleware (distributed applications); Software; Component-based software engineering; Benchmark (surveying); Software development; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002940549,0.0002912506,0.0003731876,0.000201026,0.0003770144,0.0003796889,0.0005614692,0.0000978371,0.00000404723],"category_scores_gemma":[0.00005233148,0.0002252299,0.00005272908,0.0005850151,0.0001277027,0.000626097,0.0001053747,0.0003896508,8.788182e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005892647,"about_ca_system_score_gemma":0.00007614501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002415661,"about_ca_topic_score_gemma":0.00001940419,"domain_scores_codex":[0.9985253,0.00008703826,0.0002600832,0.0004929299,0.0002175851,0.0004170324],"domain_scores_gemma":[0.9990845,0.0001776441,0.000175313,0.0002686762,0.0001637596,0.0001300756],"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":[0.000005052964,0.0001093483,0.01101548,0.000347561,0.00007153679,0.00001588703,0.004557054,0.001208553,0.003359951,0.01370268,0.00003038991,0.9655765],"study_design_scores_gemma":[0.001527244,0.001016517,0.03327071,0.002068177,0.0003110309,0.0002647972,0.007814808,0.7830776,0.07281912,0.09203671,0.002219011,0.003574294],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01658648,0.001655298,0.9805503,0.0000924624,0.00005486707,0.0001868704,0.000002954246,0.0003868167,0.0004839629],"genre_scores_gemma":[0.9473727,0.00006450884,0.05233556,0.00006333087,0.00003349583,0.00005427565,0.000009529612,0.00001733613,0.00004921054],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9620022,"threshold_uncertainty_score":0.9184611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05504768225774683,"score_gpt":0.2686966708967936,"score_spread":0.2136489886390467,"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."}}