{"id":"W4410115253","doi":"10.1109/tgrs.2025.3567357","title":"Segmentation of Individual Trees in TLS Point Clouds via Graph Optimization","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Point cloud; Segmentation; Graph; Image segmentation; Artificial intelligence; Computer vision; Theoretical computer science","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":[0.0004764044,0.001465154,0.001110988,0.001943949,0.0005581575,0.001256034,0.001339279,0.001235325,0.001908277],"category_scores_gemma":[0.00137219,0.0007359129,0.001597055,0.001501756,0.0007497947,0.001281259,0.001006784,0.001231337,0.001031422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001140851,"about_ca_system_score_gemma":0.001695529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02078669,"about_ca_topic_score_gemma":0.03372082,"domain_scores_codex":[0.9994845,0.0000651815,0.00002443122,0.0001851405,0.0001699071,0.00007075013],"domain_scores_gemma":[0.9994674,0.0001978468,0.00007334216,0.00008829036,0.0001379475,0.00003509303],"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":[0.00007538163,0.00005388187,0.001304575,0.0001050315,0.00005791198,0.00008077441,0.0001452541,0.7865829,0.01604979,0.003649806,0.002625995,0.1892687],"study_design_scores_gemma":[0.000003498453,0.000008840047,0.000222008,0.000003926655,0.000004233321,0.00001457377,0.00002444999,0.9956861,0.001857874,0.001731134,0.000438359,0.00000510195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02003591,0.00007613048,0.9760091,0.00006816356,0.00001437624,0.00006063455,0.0001994365,0.002743477,0.0007927261],"genre_scores_gemma":[0.2109231,0.0001595139,0.7848161,0.0001041802,0.00002037665,0.0001688898,0.001443311,0.0006817205,0.001682761],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02078669,"threshold_uncertainty_score":0.04133141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009452900951788513,"score_gpt":0.2379599925871938,"score_spread":0.2285070916354053,"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."}}