{"id":"W1986575376","doi":"10.1016/j.foreco.2010.01.010","title":"Using vector analysis to understand temporal changes in understorey-tree competition in agroforestry systems","year":2010,"lang":"en","type":"article","venue":"Forest Ecology and Management","topic":"Agroforestry and silvopastoral systems","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Understory; Competition (biology); Agroforestry; Tree (set theory); Ecology; Environmental science; Biology; Mathematics; Canopy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009261558,0.0001502728,0.0002585181,0.001368852,0.0002043128,0.0005114319,0.0002137536,0.0001643198,0.001254376],"category_scores_gemma":[0.002317937,0.0001130967,0.0001559272,0.001129335,0.0001449104,0.0007001918,0.0002529002,0.0002084078,0.0001410675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003278836,"about_ca_system_score_gemma":0.0002525546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009526629,"about_ca_topic_score_gemma":0.01593338,"domain_scores_codex":[0.9997258,0.0001122963,0.00002367836,0.00005158489,0.00003459545,0.00005208064],"domain_scores_gemma":[0.9984608,0.0009259229,0.0002637607,0.00007283162,0.0001663052,0.0001104165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005953127,0.0002134587,0.9107826,0.00007036182,0.0001283635,0.0000805205,0.0006796059,0.003650901,0.01268683,0.001072306,0.0003911295,0.06964878],"study_design_scores_gemma":[0.00001290126,0.0001931146,0.9457274,0.000007403264,0.0000460315,0.0001524956,0.0008667249,0.05015118,0.001157826,0.001194381,0.0004697134,0.00002079481],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951632,0.00007902355,0.004195973,0.00001542875,0.000003228294,0.000009550753,0.0002083225,0.00001795574,0.0003073232],"genre_scores_gemma":[0.9970427,0.0000347186,0.002425986,0.000003803024,0.000002566488,0.00001267871,0.0001894517,0.000005202715,0.0002827047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009526629,"threshold_uncertainty_score":0.01894236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02945656449813419,"score_gpt":0.2387691610475438,"score_spread":0.2093125965494096,"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."}}