{"id":"W4412495465","doi":"10.1016/j.geomat.2025.100064","title":"Assessing UAV-based methods for estimating tree height and crown diameter in Argane forests","year":2025,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WSP (Canada)","funders":"","keywords":"Crown (dentistry); Tree (set theory); Forestry; Remote sensing; Environmental science; Computer science; Mathematics; Geography; Materials science; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001283661,0.000615412,0.0003670342,0.001641391,0.0003339639,0.0007942122,0.0006849291,0.0005235591,0.0005283515],"category_scores_gemma":[0.002442175,0.0001620015,0.0002983265,0.0008900626,0.0001800258,0.0005357759,0.0003812723,0.0002687169,0.000271472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007751723,"about_ca_system_score_gemma":0.0007066015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0288815,"about_ca_topic_score_gemma":0.03369951,"domain_scores_codex":[0.999602,0.0001067468,0.00002363815,0.00009143857,0.0001153143,0.00006092934],"domain_scores_gemma":[0.998855,0.0005133617,0.0001680046,0.00006889315,0.0003326942,0.00006203048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000949961,0.000276885,0.1993928,0.0005523186,0.0002858155,0.0002450893,0.0004296072,0.3229084,0.01938196,0.001828832,0.001664028,0.4520844],"study_design_scores_gemma":[0.00002795075,0.0001664242,0.07934132,0.00007068652,0.00006766732,0.000143632,0.0005615441,0.910336,0.007054325,0.0005467237,0.001649663,0.00003401982],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8880169,0.002929994,0.1040815,0.0001728328,0.00008901161,0.0001006447,0.0005859452,0.0006000602,0.003423112],"genre_scores_gemma":[0.935068,0.0004336496,0.0631589,0.00002603905,0.00002218952,0.00003254515,0.0005389299,0.0000228331,0.0006969158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0288815,"threshold_uncertainty_score":0.05742675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01882556581431664,"score_gpt":0.3500347476092685,"score_spread":0.3312091817949518,"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."}}