{"id":"W2031246491","doi":"10.1016/j.agrformet.2012.06.016","title":"Predictive model for scalar concentration fluctuations in and above a model plant canopy","year":2012,"lang":"en","type":"article","venue":"Agricultural and Forest Meteorology","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Defence Research and Development Canada; University of Alberta","funders":"","keywords":"Kurtosis; Skewness; Turbulence; Mechanics; Dissipation; Environmental science; Scalar (mathematics); Turbulence kinetic energy; Stochastic modelling; Standard deviation; Statistical physics; Dispersion (optics); Mathematics; Atmospheric sciences; Meteorology; Physics; Statistics; Thermodynamics; Geometry","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":[0.00007388332,0.00009155204,0.0001171071,0.000008719758,0.00011797,0.000007191223,0.00003259887,0.00005833841,0.000005185325],"category_scores_gemma":[0.00001725311,0.0000543542,0.00001704458,0.00004425374,0.0001226233,0.0002326505,0.00005139409,0.0000490949,0.000002550265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002655561,"about_ca_system_score_gemma":0.000002913347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006917073,"about_ca_topic_score_gemma":0.0007476548,"domain_scores_codex":[0.9994356,0.00001395969,0.0001064964,0.0001490773,0.00005395798,0.0002409202],"domain_scores_gemma":[0.9998251,0.00004159034,0.0000296488,0.00003107977,0.000006166697,0.00006647321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001750409,0.0001822429,0.7943768,0.0000219958,0.0000587109,8.414859e-7,0.01493686,0.1441219,0.02719483,0.01290837,0.004043734,0.001978689],"study_design_scores_gemma":[0.0003190485,0.00006014062,0.5858896,0.000002389159,0.00001579454,0.000006089855,0.0001682452,0.4111514,0.0000849628,0.002157726,0.00006519974,0.0000793982],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959981,0.0001962679,0.00242533,0.0005773596,0.00003678051,0.0002769514,0.00006573402,0.00001033423,0.0004131585],"genre_scores_gemma":[0.9984697,0.00008021916,0.0009682691,0.0001432373,0.00004103035,0.00008911617,0.00003689042,0.00000246389,0.0001691253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2670295,"threshold_uncertainty_score":0.22165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01073107954738097,"score_gpt":0.2069092807353559,"score_spread":0.196178201187975,"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."}}