{"id":"W2023705343","doi":"10.1007/s00348-005-0017-5","title":"A variational filtration and interpolation technique for PIV employing fluid dynamical constraints","year":2005,"lang":"en","type":"article","venue":"Experiments in Fluids","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Particle image velocimetry; Spurious relationship; Interpolation (computer graphics); Vector field; Vortex; Smoothness; Velocimetry; Field (mathematics); Computer science; Physics; Algorithm; Mathematical analysis; Mechanics; Mathematics; Image (mathematics); Turbulence; Computer vision","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001424852,0.0001329986,0.0001207275,0.0001227326,0.00004307669,0.00003898301,0.0000651338,0.0001020497,0.00008338004],"category_scores_gemma":[0.00002251941,0.0001493859,0.00002977502,0.00007073434,0.0000352664,0.000197128,0.00001995131,0.00008454415,0.000004679987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000171321,"about_ca_system_score_gemma":0.00001887463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003949966,"about_ca_topic_score_gemma":0.000005700603,"domain_scores_codex":[0.9992586,0.00001376379,0.0002728308,0.0001752214,0.0001015637,0.0001779585],"domain_scores_gemma":[0.9997788,0.00004386706,0.00001440916,0.00009836614,0.00002118159,0.0000433428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003470105,0.00009683647,0.001279928,0.00003699791,0.00003779316,0.000001397814,0.00121761,0.01323742,0.9500094,0.0279084,0.0004321885,0.00570733],"study_design_scores_gemma":[0.000597506,0.00003690227,0.0009941772,0.00003672172,0.000003589628,0.00000638854,0.00002182678,0.984706,0.01249067,0.0004823961,0.000459527,0.0001642603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2454835,0.0003611264,0.7504266,0.00009753228,0.0003536699,0.000850923,0.00004075412,0.0001739651,0.00221187],"genre_scores_gemma":[0.9413793,0.00001526968,0.058037,0.00004474553,0.00009669708,0.0002873932,0.00007602762,0.00002549234,0.00003808123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9714686,"threshold_uncertainty_score":0.6091779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01084090652318786,"score_gpt":0.2570832710101089,"score_spread":0.246242364486921,"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."}}