{"id":"W4230312528","doi":"10.24124/2009/bpgub612","title":"Numerical modelling of airflow within and above forests and forest clearings using computational fluid dynamics.","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Tree Root and Stability Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"University of Northern British Columbia","keywords":"Clearing; Environmental science; Wind speed; Computational fluid dynamics; Canopy; Tree canopy; Turbulence kinetic energy; Airflow; Meteorology; Turbulence; Atmospheric sciences; Tree (set theory); Wind direction; Hydrology (agriculture); Geography; Geology; Mathematics; Engineering; Mechanics; Physics; Geotechnical engineering","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":[0.00006380603,0.0002273112,0.0003743218,0.000101465,0.00006860091,0.00002893513,0.00004683278,0.0001521274,0.000002001293],"category_scores_gemma":[0.00001076607,0.0002262519,0.00004753086,0.00008223979,0.0000350519,0.00009158249,0.00001135782,0.000165122,3.351709e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005092807,"about_ca_system_score_gemma":0.00001738155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002444512,"about_ca_topic_score_gemma":0.01570326,"domain_scores_codex":[0.9991401,0.000007372303,0.0003309059,0.00021044,0.0001594101,0.0001517325],"domain_scores_gemma":[0.9996774,0.0000627949,0.00005674666,0.00007759157,0.00007425646,0.00005124014],"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":[0.00003643341,0.00001143811,0.01376107,0.0003784776,0.000061655,0.000001127219,0.000879435,0.9818501,0.000006382641,0.0009023948,0.000009793835,0.002101635],"study_design_scores_gemma":[0.0001675007,0.00003116418,0.09660891,0.00009927403,0.00003959689,0.000003133295,0.0002900267,0.8990253,0.00002220962,0.003520359,0.000001597789,0.0001909627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.903749,0.0006950891,0.09449109,0.000008573042,0.0001077758,0.000140508,0.00001195743,0.00007723528,0.000718699],"genre_scores_gemma":[0.9890806,0.00002916242,0.01062371,0.000002502156,0.00002324,0.000002667097,0.0001427713,0.00003229736,0.0000630444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08533154,"threshold_uncertainty_score":0.9226284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459515787272318,"score_gpt":0.2264403575151356,"score_spread":0.2118451996424124,"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."}}