{"id":"W4388408204","doi":"10.3390/rs15215261","title":"Combination of UAV Photogrammetry and Field Inventories Enables Description of Height–Diameter Relationship within Semi-Arid Silvopastoral Systems","year":2023,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Agroforestry and silvopastoral systems","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"Iran National Science Foundation; National Science Foundation","keywords":"Diameter at breast height; Coppicing; Biomass (ecology); Forestry; Photogrammetry; Forest inventory; Crown (dentistry); Range (aeronautics); Arid; Geography; Environmental science; Physical geography; Agroforestry; Ecology; Remote sensing; Forest management; Biology; Woody plant","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":[0.0003199769,0.0003506583,0.000362386,0.001352867,0.0001778638,0.0004981048,0.0002534573,0.0001664059,0.0006025829],"category_scores_gemma":[0.0003779276,0.0002094123,0.0002133383,0.0009850416,0.0001576944,0.0004185756,0.0003318258,0.00012632,0.0002115833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002559569,"about_ca_system_score_gemma":0.0001275246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007355722,"about_ca_topic_score_gemma":0.02763357,"domain_scores_codex":[0.9997432,0.00003532139,0.00001831024,0.0001144201,0.00004598995,0.00004269916],"domain_scores_gemma":[0.9996964,0.00007016295,0.00009987975,0.00005550887,0.00005995377,0.00001821277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001068326,0.00008542545,0.8533037,0.0001604374,0.0001745973,0.0001387592,0.0003500031,0.003928688,0.03996772,0.0001125856,0.0002356759,0.1014356],"study_design_scores_gemma":[0.000002005033,0.0000338022,0.9946075,0.00001057897,0.00002302528,0.00007989394,0.0001395358,0.003667113,0.001029238,0.0000299127,0.0003715192,0.00000592218],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951994,0.0002534971,0.003158783,0.000006634253,0.000004617329,0.00001185542,0.0004084301,0.00004567491,0.0009111431],"genre_scores_gemma":[0.9934163,0.0001277505,0.005712862,0.000008177203,0.00000562071,0.000009030482,0.0005319628,0.000007866182,0.0001804716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007355722,"threshold_uncertainty_score":0.01462579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04818222698354942,"score_gpt":0.2293942120831035,"score_spread":0.1812119850995541,"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."}}