{"id":"W2564893059","doi":"","title":"Tree Roots in Agroforestry: Evaluating Biomass and Distribution with Ground Penetrating Radar","year":2013,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Tree Root and Stability Studies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agriculture and Agri-Food Canada","keywords":"Biomass (ecology); Agroforestry; Distribution (mathematics); Environmental science; Ground-penetrating radar; Tree (set theory); Forestry; Geography; Ecology; Radar; Biology; Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001501343,0.0002893584,0.0003095044,0.00006862359,0.00009321252,0.00007434108,0.000069627,0.0001707354,0.00001363058],"category_scores_gemma":[0.00005059041,0.000258356,0.000029166,0.0001923486,0.00002659218,0.0001159512,0.00001325733,0.0002531616,0.000005031602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001094182,"about_ca_system_score_gemma":0.00002838565,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008828919,"about_ca_topic_score_gemma":0.09017452,"domain_scores_codex":[0.998973,0.00002958883,0.0002246679,0.0002627284,0.0002230972,0.0002869033],"domain_scores_gemma":[0.9995916,0.00008415319,0.00006814679,0.0001548063,0.00005245622,0.00004876482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005990171,0.0002596132,0.4828946,0.01489641,0.001162626,0.0001026072,0.07113194,0.00112324,0.1411474,0.001404468,0.003334936,0.2819431],"study_design_scores_gemma":[0.0004396272,0.00009297092,0.9881095,0.000348683,0.00004775727,0.000002510623,0.008224254,0.001860565,0.0003810076,0.0001061013,0.00004762368,0.0003394406],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936421,0.002034293,0.00005607131,0.0000263561,0.0001578201,0.000341464,0.00001091336,0.0001306052,0.003600355],"genre_scores_gemma":[0.9979591,0.0000313015,0.000310289,6.287756e-7,0.00004968039,0.00007230155,0.0008099831,0.00004074844,0.0007259368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5052149,"threshold_uncertainty_score":0.9999869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01869580099399575,"score_gpt":0.2947959160160608,"score_spread":0.276100115022065,"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."}}