{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004233201,0.00009968362,0.0001235377,0.0005204563,0.0002152682,0.00007366967,0.0001825118,0.00005263636,0.000001289777],"category_scores_gemma":[0.000004152138,0.00009265121,0.00004554139,0.001345522,0.0001553984,0.0003985444,0.000004239649,0.0001179787,4.941754e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001675273,"about_ca_system_score_gemma":0.00004442046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000105868,"about_ca_topic_score_gemma":0.00005167303,"domain_scores_codex":[0.9990384,0.00008591769,0.0002254339,0.0002904575,0.0001921605,0.000167642],"domain_scores_gemma":[0.9995962,0.00007846914,0.00006242841,0.0001833256,0.00004330604,0.00003621567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009740811,0.000041048,0.000002588183,0.000008915659,0.000007631124,0.000003305665,0.001181228,0.06370689,0.007058762,0.0002759048,9.049497e-7,0.9277031],"study_design_scores_gemma":[0.0003519456,0.00007870588,0.000608851,0.0001256595,0.0000121849,0.00001504228,0.0002867843,0.92744,0.06297473,0.007992385,0.000001837277,0.0001118923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06218033,0.00002153694,0.9369023,0.0002170965,0.0004362182,0.0001136403,0.000002080423,0.00003563851,0.00009113683],"genre_scores_gemma":[0.7530745,0.00004709886,0.2466928,0.0001382427,0.000003982731,1.229446e-7,5.085128e-7,0.000002323092,0.00004039755],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9275912,"threshold_uncertainty_score":0.3778207,"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."}}