{"id":"W2096226167","doi":"10.1109/issre.2003.1251027","title":"A comprehensive and systematic methodology for client-server class integration testing","year":2005,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Class (philosophy); Context (archaeology); Client–server model; Data mining; Server; Database; Artificial intelligence; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0251837,0.002728123,0.00254416,0.007787231,0.00199993,0.005356996,0.005894163,0.002630131,0.002847305],"category_scores_gemma":[0.03867185,0.002153007,0.002508931,0.003632254,0.005079355,0.006008173,0.004939588,0.004678633,0.001881112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002216521,"about_ca_system_score_gemma":0.0106658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001923743,"about_ca_topic_score_gemma":0.002937301,"domain_scores_codex":[0.9602656,0.01660652,0.004381946,0.002521997,0.01555155,0.000672321],"domain_scores_gemma":[0.9714139,0.0103311,0.002030493,0.007486818,0.008181455,0.0005561516],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007626913,0.0009104146,0.004061597,0.003773274,0.0003422398,0.001006844,0.005256298,0.03155583,0.02488529,0.2501923,0.007320181,0.6706195],"study_design_scores_gemma":[0.0002954885,0.001834726,0.005289475,0.008466912,0.0007057535,0.01007579,0.00436388,0.2791483,0.07125399,0.3788849,0.2388268,0.0008539796],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002961145,0.0001100492,0.9984335,0.00007510467,0.000008987545,0.0003401547,0.00002471562,0.0003856176,0.0003256657],"genre_scores_gemma":[0.00714553,0.0002132286,0.991297,0.00006715226,0.00001390412,0.0007219149,0.0001055566,0.0001146083,0.0003210754],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0251837,"threshold_uncertainty_score":0.1331857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1683341546886251,"score_gpt":0.3493839636123504,"score_spread":0.1810498089237253,"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."}}