{"id":"W2910240344","doi":"10.2514/6.2019-2222","title":"The Mosaic CGNS Dataflow Platform","year":2019,"lang":"en","type":"article","venue":"AIAA Scitech 2019 Forum","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Dataflow; Mosaic; Computer science; Embedded system; Programming language; History","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001337376,0.0005217845,0.0004773754,0.0006741407,0.0006424874,0.001815194,0.001930983,0.0004295075,0.02471392],"category_scores_gemma":[0.003150521,0.000409083,0.0004124777,0.0005999631,0.0005971478,0.001871999,0.001754613,0.001136414,0.004674072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001520638,"about_ca_system_score_gemma":0.002797651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01150004,"about_ca_topic_score_gemma":0.008755095,"domain_scores_codex":[0.9993069,0.00006235785,0.00003083548,0.0001662494,0.0003063696,0.0001272759],"domain_scores_gemma":[0.9988828,0.000118837,0.00004324327,0.0004304723,0.0002952287,0.0002293932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004281362,0.0007578721,0.006555063,0.0004147764,0.0002142335,0.0003167469,0.0004465103,0.04756161,0.07332866,0.1103233,0.4424286,0.3133714],"study_design_scores_gemma":[0.000768875,0.0005259232,0.002844851,0.0000987441,0.00007877094,0.0002147372,0.000133103,0.4990136,0.05642824,0.05422152,0.3855309,0.000140669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1197896,0.001247642,0.406941,0.002711755,0.001835054,0.001594802,0.01606679,0.2559773,0.193836],"genre_scores_gemma":[0.6182014,0.0008760507,0.2570825,0.001636167,0.0004733625,0.0007398261,0.04033597,0.01045939,0.07019537],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02471392,"threshold_uncertainty_score":0.08267623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009831651047282952,"score_gpt":0.2398260214516423,"score_spread":0.2299943704043593,"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."}}