{"id":"W2088518721","doi":"10.1007/s003489900085","title":"Comparison of Gaussian particle center estimators and the achievable measurement density for particle tracking velocimetry","year":2000,"lang":"en","type":"article","venue":"Experiments in Fluids","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Particle tracking velocimetry; Estimator; Gaussian; Particle image velocimetry; Physics; Velocimetry; Gaussian filter; Pixel; Displacement (psychology); Optics; Algorithm; Mathematics; Statistics; Turbulence; Mechanics","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":[0.0003532233,0.000127394,0.0002390992,0.00002087575,0.00007093359,0.00003224922,0.0001038241,0.00004297533,0.00005949613],"category_scores_gemma":[0.00001893745,0.0001014159,0.00004829271,0.00009869454,0.00007434886,0.00008828694,0.00002045413,0.00007688629,0.000005398257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007980126,"about_ca_system_score_gemma":0.000009061314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002720411,"about_ca_topic_score_gemma":0.00001065361,"domain_scores_codex":[0.9990265,0.00003302104,0.0003306534,0.0001459691,0.0002035787,0.0002602514],"domain_scores_gemma":[0.9996815,0.00003672592,0.00001779065,0.0001891652,0.0000216714,0.00005315123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001520341,0.001942944,0.4942288,0.0003614908,0.0005254849,0.000008063957,0.02829939,0.1223451,0.2756014,0.01544742,0.001685369,0.05803429],"study_design_scores_gemma":[0.002560763,0.00004139077,0.01039902,0.00004037021,0.00001321741,9.835924e-7,0.0001162057,0.8270508,0.159179,0.00009592853,0.0003787355,0.0001235305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958234,0.00189284,0.001257848,0.00005757416,0.0001436631,0.0003234624,0.000003988883,0.0000422818,0.000454879],"genre_scores_gemma":[0.9988006,0.00002888237,0.001018026,0.00002759968,0.0000192872,0.0000514612,0.000002244139,0.00002096636,0.00003094878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7047057,"threshold_uncertainty_score":0.4135622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03008598118570631,"score_gpt":0.2874396297375954,"score_spread":0.2573536485518891,"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."}}