{"id":"W2970564614","doi":"10.1088/1742-6596/1001/1/012018","title":"Towards the computation of time-periodic inertial range dynamics","year":2018,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Turbulence; Inertial frame of reference; Computation; Invariant (physics); Vortex; Physics; Forcing (mathematics); Classical mechanics; Bifurcation; Mechanics; Mathematical analysis; Computer science; Mathematics; Algorithm; Nonlinear system","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":[0.0002033292,0.0002586404,0.0002304026,0.0004536754,0.0002308012,0.0005554121,0.0003990944,0.0004428276,0.0009794146],"category_scores_gemma":[0.001332162,0.000171673,0.0002201078,0.0002780299,0.0003994462,0.0004696731,0.0005058226,0.000382772,0.0002158424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001765838,"about_ca_system_score_gemma":0.0003642241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121947,"about_ca_topic_score_gemma":0.0008083381,"domain_scores_codex":[0.9999403,0.00001545196,0.00000415464,0.000007979074,0.00002449613,0.000007619773],"domain_scores_gemma":[0.9997599,0.00009627624,0.00003350206,0.00004029552,0.00003951497,0.00003055831],"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":[0.000150789,0.0001006432,0.003641058,0.0001358887,0.0000531257,0.000254393,0.0003163216,0.8203528,0.05191716,0.0578156,0.0009488749,0.06431341],"study_design_scores_gemma":[0.000003660496,0.000009049651,0.0001510724,0.000002631056,0.000001140134,0.00001021579,0.000006530757,0.9957273,0.001011693,0.002853587,0.0002215098,0.000001698216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.386494,0.0001794118,0.607659,0.0001781915,0.00004378377,0.00005725542,0.00008633495,0.0005796412,0.004722257],"genre_scores_gemma":[0.7664072,0.0001655425,0.2320202,0.00003082648,0.00002172864,0.00007077542,0.0001064348,0.0001085263,0.001068767],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00121947,"threshold_uncertainty_score":0.003276527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02359192417580017,"score_gpt":0.2761497599262904,"score_spread":0.2525578357504903,"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."}}