{"id":"W3080269115","doi":"10.1175/jpo-d-19-0299.1","title":"Effects of Adding Forced Near-Inertial Motion to a Wind-Driven Channel Flow","year":2020,"lang":"en","type":"article","venue":"Journal of Physical Oceanography","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kinetic energy; Mechanics; Geostrophic wind; Physics; Range (aeronautics); Turbulence; Turbulence kinetic energy; Reynolds number; Energy–depth relationship in a rectangular channel; Low frequency; Flow (mathematics); Reynolds stress; RADIUS; Computational physics; Open-channel flow; Classical mechanics; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003344912,0.0005284096,0.0004633978,0.0003369059,0.000590943,0.001101415,0.0005563349,0.0008759935,0.002764748],"category_scores_gemma":[0.00231791,0.000333875,0.0006136786,0.0002179214,0.0006916124,0.0005970431,0.000849026,0.0008094867,0.0001723949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006153331,"about_ca_system_score_gemma":0.0006702486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01203053,"about_ca_topic_score_gemma":0.006701565,"domain_scores_codex":[0.9998347,0.0000416789,0.00001485231,0.0000277976,0.00002979216,0.00005111322],"domain_scores_gemma":[0.9990362,0.0005186349,0.00008844851,0.00008638749,0.0001103748,0.0001599094],"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":[0.0009296573,0.0004250722,0.008306924,0.00008557962,0.0001103168,0.0003934606,0.00005446785,0.9647945,0.02004902,0.0008260949,0.0003387861,0.003686156],"study_design_scores_gemma":[0.0001368142,0.0006022929,0.007282954,0.00001701396,0.00006409012,0.00003408147,0.00006085699,0.9816929,0.009414854,0.0002542992,0.0004004212,0.00003942243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964178,0.00002831134,0.001044846,0.00007170789,0.00004954084,0.00002352809,0.0001230455,0.0001012978,0.002139955],"genre_scores_gemma":[0.9992653,0.00001572205,0.0003584644,0.0000226542,0.000004421474,0.000008487184,0.00005521571,0.0000121097,0.0002576628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01203053,"threshold_uncertainty_score":0.02392095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007169861693947875,"score_gpt":0.1980232051354763,"score_spread":0.1908533434415284,"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."}}