{"id":"W9941716","doi":"10.20659/jfp.13.special_issue_279","title":"Stability of Surface LiDAR Height Estimates on a Point and Polygon Basis(&lt;Special Issue&gt;Silvilaser)","year":2008,"lang":"en","type":"article","venue":"Journal of Forest Planning","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; University of British Columbia; Canadian Forest Service","funders":"","keywords":"Lidar; Polygon (computer graphics); Remote sensing; Environmental science; Consistency (knowledge bases); Tree canopy; Forest inventory; Ranging; Canopy; Mathematics; Geography; Geodesy; Computer science; Forest management; Geometry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003480028,0.0001502446,0.0002900237,0.001647545,0.0002697118,0.001113173,0.0004419437,0.0002135906,0.001041616],"category_scores_gemma":[0.01189476,0.0001475202,0.0002266164,0.001825454,0.0003193287,0.0007121473,0.0007135053,0.000290769,0.0005545071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004963519,"about_ca_system_score_gemma":0.000481175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01619175,"about_ca_topic_score_gemma":0.02337706,"domain_scores_codex":[0.9980677,0.0003409683,0.0001960341,0.0004486652,0.0008521384,0.00009445575],"domain_scores_gemma":[0.9899921,0.003268804,0.001717388,0.001187037,0.003715016,0.0001196064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003057711,0.00002608311,0.8722917,0.00005141178,0.0001854505,0.00009610822,0.0004554106,0.01024839,0.007271153,0.0003884073,0.001743698,0.1069364],"study_design_scores_gemma":[0.000009835288,0.00010072,0.9534851,0.0000237015,0.00004045711,0.0001979733,0.0005200487,0.03889103,0.004248784,0.0002731716,0.002177538,0.00003157818],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758178,0.0001895061,0.01781541,0.00006248496,0.00002672779,0.00004195931,0.002684665,0.0002563656,0.003104949],"genre_scores_gemma":[0.9870386,0.00005179542,0.009737344,0.000018254,0.00001291028,0.00001897915,0.002497679,0.00005768655,0.0005666304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01619175,"threshold_uncertainty_score":0.03219503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0158835017619912,"score_gpt":0.2410187735417626,"score_spread":0.2251352717797714,"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."}}