{"id":"W2139754501","doi":"10.1023/a:1026328920674","title":"Level Set Curve Matching and Particle Image Velocimetry for Resolving Chemistry and Turbulence Interactions in Propagating Flames","year":2003,"lang":"en","type":"article","venue":"Journal of Mathematical Imaging and Vision","topic":"Radiative Heat Transfer Studies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Particle image velocimetry; Turbulence; Vector field; Planar laser-induced fluorescence; Diffusion flame; Combustion; Image processing; Mechanics; Computation; Chemistry; Physics; Algorithm; Image (mathematics); Optics; Computer science; Laser-induced fluorescence; Computer vision; Laser; Combustor","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":[0.001308763,0.0004440761,0.0009224319,0.002559575,0.000855809,0.001392163,0.001139209,0.00136394,0.001016834],"category_scores_gemma":[0.004364802,0.000676523,0.0007217458,0.001365608,0.0008050891,0.001852065,0.00115121,0.0009063904,0.0002645154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001018951,"about_ca_system_score_gemma":0.001771394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006158036,"about_ca_topic_score_gemma":0.005071017,"domain_scores_codex":[0.9996269,0.0000828312,0.00002596644,0.00004024753,0.0001780643,0.00004601447],"domain_scores_gemma":[0.9987714,0.0005763097,0.0001236652,0.0001539575,0.0002877826,0.00008686052],"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":[0.0009706993,0.0004325808,0.006812949,0.0001189679,0.0001231001,0.0001169534,0.0001815127,0.523041,0.07804015,0.01989891,0.001194286,0.369069],"study_design_scores_gemma":[0.00000765322,0.000009456361,0.0003421154,9.497253e-7,0.000004400822,0.000007975975,0.000005329704,0.9916551,0.006349981,0.001534372,0.00007649633,0.00000609966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1862959,0.0001366054,0.8112385,0.0001673993,0.00003724718,0.00007457459,0.00007722022,0.001281487,0.0006911722],"genre_scores_gemma":[0.6197234,0.0001200349,0.3785063,0.00005574938,0.00002522161,0.00007142473,0.0001506299,0.0002500658,0.001097295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006158036,"threshold_uncertainty_score":0.01224434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02454573934326763,"score_gpt":0.3181278833553183,"score_spread":0.2935821440120507,"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."}}