{"id":"W2023630976","doi":"10.1109/mcse.2009.204","title":"Scientific and Engineering Computing Using ATI Stream Technology","year":2009,"lang":"en","type":"article","venue":"Computing in Science & Engineering","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Computer science; Stream processing; Data science; Computational science; Parallel computing","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":[0.001815983,0.0003095922,0.0003191091,0.001872024,0.0005810678,0.0009971733,0.001724266,0.00008326704,4.169722e-7],"category_scores_gemma":[0.0003015659,0.0003319698,0.00004735608,0.005298534,0.000217965,0.0001960894,0.001256253,0.0004075131,0.000003131049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002389182,"about_ca_system_score_gemma":0.00009503336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001048497,"about_ca_topic_score_gemma":5.41855e-7,"domain_scores_codex":[0.9967942,0.00001679634,0.0004778599,0.001075239,0.0005539146,0.00108202],"domain_scores_gemma":[0.9987491,0.000112698,0.0001213104,0.0007174617,0.0001169132,0.000182503],"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":[4.09733e-7,0.00002958666,0.002103085,0.00001531502,0.000003075878,0.0000294126,0.000674077,0.9243619,0.02208266,0.02383554,0.000003032979,0.02686191],"study_design_scores_gemma":[0.0002157685,0.00004317339,0.0178652,0.0002925972,0.000003038053,0.0000789839,0.00004937086,0.9791288,0.001628889,0.0001519946,0.0001824087,0.0003598211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6776541,0.0002311456,0.3206143,0.0001608101,0.000589911,0.0001254806,1.065346e-7,0.0005475282,0.00007659059],"genre_scores_gemma":[0.8551377,8.381652e-7,0.1447213,0.0000366434,0.00008329935,5.069227e-7,1.924308e-7,0.00001212118,0.000007416702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1774835,"threshold_uncertainty_score":0.9999132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01068737141673781,"score_gpt":0.2314831508765545,"score_spread":0.2207957794598167,"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."}}