{"id":"W2105362824","doi":"10.1109/ainaw.2007.141","title":"Database-Driven Grid Computing with GridBASE","year":2007,"lang":"en","type":"article","venue":"","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Computer science; Grid computing; Grid; Scalability; Distributed computing; Workflow; Component (thermodynamics); Database; Semantic grid; Software deployment; DRMAA; Software engineering; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007204272,0.000167487,0.000174265,0.00009402369,0.0001777642,0.0001908655,0.0009244188,0.00003868746,0.00001208937],"category_scores_gemma":[0.00001472719,0.0001253603,0.00004198278,0.0005433461,0.00003594976,0.0002927929,0.0002898391,0.0001486042,0.0001459823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003082726,"about_ca_system_score_gemma":0.00005714563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001049187,"about_ca_topic_score_gemma":0.00004523353,"domain_scores_codex":[0.9984011,0.00004206315,0.0002784336,0.0004390102,0.0003508775,0.0004885263],"domain_scores_gemma":[0.9987673,0.0001796787,0.0001056511,0.0006686328,0.00009712877,0.000181606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001400644,0.000939492,0.09401524,0.0003082854,0.0003308885,0.00278701,0.003413636,0.03782586,0.004436116,0.6342773,0.1407804,0.08074565],"study_design_scores_gemma":[0.0023637,0.0005106586,0.01738161,0.0003662722,0.00002064304,0.0008537397,0.0002337747,0.8622174,0.002969275,0.0002124866,0.1114141,0.001456391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03172727,0.00003113734,0.9490865,0.0001842689,0.0006060231,0.0001268834,0.000006130298,0.0005868933,0.01764487],"genre_scores_gemma":[0.8788427,5.460407e-7,0.1202126,0.0003477597,0.0003225472,6.431464e-7,0.00002961727,0.000008762851,0.0002348348],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8471155,"threshold_uncertainty_score":0.5112045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01370581406569654,"score_gpt":0.2437065978523263,"score_spread":0.2300007837866297,"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."}}