{"id":"W2030685115","doi":"10.1088/1742-6596/256/1/012007","title":"Accelerated Synchrotron X-ray Diffraction Data Analysis on a Heterogeneous High Performance Computing System","year":2010,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Synchrotron; Software; Xeon Phi; Supercomputer; Computational science; Data analysis; Computer science; IBM; Diffraction; Computation; Operating system; Materials science; Optics; Data mining; Physics; Nanotechnology; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.0005465229,0.0001897897,0.0004102591,0.0002058321,0.0002812186,0.0004577854,0.001583877,0.00007447977,0.000005462066],"category_scores_gemma":[0.00004238509,0.000160258,0.00008982007,0.000702988,0.00005457601,0.001447263,0.0002863012,0.0005784308,0.000005950072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004342339,"about_ca_system_score_gemma":0.0001493789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001622961,"about_ca_topic_score_gemma":0.000003742633,"domain_scores_codex":[0.9984401,0.0001238112,0.0004963495,0.0003109575,0.0004120185,0.0002167971],"domain_scores_gemma":[0.9975137,0.00009101546,0.0008323887,0.0008675443,0.0006080064,0.00008738895],"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":[0.0001511768,0.0004107615,0.002249782,0.0001454045,0.00107722,0.00006481387,0.001200821,0.6353406,0.02125982,0.05178657,0.0002576832,0.2860554],"study_design_scores_gemma":[0.0002104341,0.0003266911,0.005695404,0.0001010738,0.0001013487,0.00006629945,0.00003784187,0.9522361,0.04067591,0.000233576,0.00009153416,0.0002237603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3368106,0.000006701054,0.6624228,0.00009608592,0.0003865621,0.00005154858,0.000003480371,0.0001205163,0.0001016726],"genre_scores_gemma":[0.9284538,0.00002410141,0.07119296,0.00003527872,0.0002534951,8.430336e-7,0.00001325566,0.000008669993,0.0000176075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5916432,"threshold_uncertainty_score":0.6535134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0343443754869152,"score_gpt":0.2737654431020503,"score_spread":0.239421067615135,"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."}}