{"id":"W4401052513","doi":"10.1061/jhend8.hyeng-13675","title":"Characterizing Flow Patterns and Velocities in a Backwater Valve Using Fluorescent Particle Tracers for Image Velocimetry","year":2024,"lang":"en","type":"article","venue":"Journal of Hydraulic Engineering","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Chiropractic Association; University of Guelph","funders":"","keywords":"Particle image velocimetry; Particle tracking velocimetry; Velocimetry; Geology; Particle (ecology); Flow (mathematics); Mechanics; Turbulence; Physics; Oceanography","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":[0.0004553715,0.0002052214,0.0003658158,0.0002520604,0.00002428392,0.0001435445,0.00009821688,0.00007785645,0.00001436242],"category_scores_gemma":[0.00003650271,0.000186914,0.0001530878,0.0001608804,0.00001323189,0.0004166554,0.00001754114,0.0002564737,0.000003186169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001646123,"about_ca_system_score_gemma":0.00002310006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001134019,"about_ca_topic_score_gemma":0.000002143842,"domain_scores_codex":[0.9987425,0.0000156563,0.0006060981,0.0001216868,0.0001710662,0.0003429686],"domain_scores_gemma":[0.9995849,0.0001338108,0.00004699281,0.00009056034,0.00002911438,0.0001146803],"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":[0.00002921022,0.00003648032,0.001397175,0.006001856,0.0006479817,0.0004066683,0.01582479,0.636148,0.3169427,0.00005333489,0.0002555746,0.02225613],"study_design_scores_gemma":[0.0003817134,0.00003883531,0.002033348,0.001363292,0.00004696719,0.0003447557,0.0003723918,0.978663,0.01546727,0.00001241057,0.001058197,0.0002178599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8795779,0.002441971,0.1166187,0.00008744683,0.001009654,0.0001492897,0.00001039548,0.00008079435,0.00002378924],"genre_scores_gemma":[0.9930141,0.0001585471,0.006347328,0.0000191945,0.0003743049,0.000009315439,0.000001773337,0.00006903952,0.000006382685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3425149,"threshold_uncertainty_score":0.7622131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223361633829121,"score_gpt":0.2276197703501269,"score_spread":0.2153861540118357,"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."}}