{"id":"W3200580391","doi":"10.1002/esp.5251","title":"Large‐scale turbulent mixing at a mesoscale confluence assessed through drone imagery and eddy‐resolved modelling","year":2021,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mesoscale meteorology; Geology; Turbulence; Vortex; Downwelling; Confluence; Mixing (physics); Mechanics; Geometry; Eddy; Physics; Geophysics; Meteorology; Upwelling","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000309515,0.0002606047,0.0003258202,0.00001327821,0.0004905383,0.00008894867,0.0001178721,0.0001412711,0.001116134],"category_scores_gemma":[0.00002505197,0.0002060088,0.00003827224,0.0002519614,0.0002326634,0.000739025,0.0001536996,0.0002019604,0.00004523765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001569396,"about_ca_system_score_gemma":0.00004764801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008958633,"about_ca_topic_score_gemma":0.0005942558,"domain_scores_codex":[0.9982337,0.00003216809,0.0002859308,0.000628391,0.0002955523,0.0005243027],"domain_scores_gemma":[0.9994032,0.0001153331,0.00009001243,0.0001870268,0.00004238708,0.0001619955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007790388,0.001020993,0.8071294,0.002392062,0.0002080588,0.0005760469,0.03150607,0.122213,0.03242043,0.0001106033,0.0006298728,0.001014401],"study_design_scores_gemma":[0.01134118,0.0008013225,0.07515176,0.0009911408,0.000560258,0.001072454,0.007458934,0.1696148,0.467344,0.007592869,0.2535347,0.004536539],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734999,0.005354332,0.01904718,0.0005686426,0.00004255379,0.0001588258,0.00001926067,0.00007370549,0.00123559],"genre_scores_gemma":[0.9894582,0.002621139,0.005370446,0.0006353821,0.0000227181,0.0000117935,0.00004837708,0.00002138002,0.001810549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7319777,"threshold_uncertainty_score":0.999797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01102337512975243,"score_gpt":0.2174261705034457,"score_spread":0.2064027953736933,"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."}}