{"id":"W2167233120","doi":"10.1109/mdso.2006.66","title":"Grid Computing Gets Small","year":2006,"lang":"en","type":"article","venue":"IEEE Distributed Systems Online","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Interoperability; Provisioning; Grid computing; Grid; Middleware (distributed applications); Bandwidth (computing); Interface (matter); Semantic grid; Cloud computing; World Wide Web; Telecommunications; Distributed computing; Operating system; Semantic Web","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":[0.0007425162,0.0004997984,0.0007062832,0.0001602578,0.0003691745,0.0006924227,0.001871286,0.0002367636,0.000002554829],"category_scores_gemma":[0.00004824647,0.0004758404,0.0002345624,0.000703371,0.00006199514,0.0002550663,0.000235222,0.0003733894,0.0001800623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001834846,"about_ca_system_score_gemma":0.0001416861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001222043,"about_ca_topic_score_gemma":0.00008697929,"domain_scores_codex":[0.9959559,0.0003194495,0.001214818,0.0009291154,0.0005893469,0.0009913432],"domain_scores_gemma":[0.9973608,0.0002423063,0.0005505815,0.001190748,0.0004205659,0.0002349443],"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":[0.0000417924,0.002409536,0.01209331,0.000859379,0.0003667076,0.001388197,0.0004560041,0.7515996,0.003313001,0.06547479,0.155305,0.006692674],"study_design_scores_gemma":[0.001463398,0.0001320815,0.008273305,0.0004463765,0.00003050072,0.0004088614,0.00009186412,0.8298132,0.0002348556,0.0004306461,0.1575445,0.001130428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1263509,0.001140765,0.8619995,0.0002803555,0.006226928,0.0004453661,0.001427335,0.001257825,0.0008710247],"genre_scores_gemma":[0.991004,0.000005239875,0.003196661,0.00007631072,0.002626221,0.00001253373,0.002610531,0.00003408024,0.0004344606],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8646531,"threshold_uncertainty_score":0.9997693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024270147660415,"score_gpt":0.2415654542950476,"score_spread":0.2213227528184434,"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."}}