{"id":"W2046759104","doi":"10.5589/m11-041","title":"Detection of small single trees in the forest–tundra ecotone using height values from airborne laser scanning","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Norges Miljø- og Biovitenskapelige Universitet; Norges Forskningsråd","keywords":"Tundra; Ecotone; Scots pine; Tree line; Transect; Crown (dentistry); Alpine climate; Laser scanning; Lidar; Taiga; Diameter at breast height; Physical geography; Forestry; Environmental science; Geography; Tree (set theory); Remote sensing; Arctic; Ecology; Mathematics; Climate change; Laser; Pinus <genus>; Shrub; Physics; Biology; Botany","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004287494,0.0001251836,0.0002002956,0.0001741243,0.0001870201,0.00003916472,0.0001876986,0.00007677556,0.00002708515],"category_scores_gemma":[0.00007258522,0.0001030774,0.00009164084,0.0003551534,0.0002258695,0.0001387506,0.00001528602,0.0002394053,0.000006211634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002908771,"about_ca_system_score_gemma":0.00009945202,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1820004,"about_ca_topic_score_gemma":0.4291208,"domain_scores_codex":[0.9988762,0.0001284427,0.0003966562,0.0001513921,0.0001742501,0.0002731311],"domain_scores_gemma":[0.999147,0.00007126841,0.0003126389,0.0002414575,0.00003958813,0.000188032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00005557095,0.00004129309,0.006958378,0.00000887303,0.00006114127,0.0003434413,0.02273848,0.01008843,0.1320264,0.000006239443,0.00008427831,0.8275875],"study_design_scores_gemma":[0.001506664,0.0005137329,0.4466682,0.001320118,0.0003483829,0.002026519,0.01087819,0.2487662,0.2664793,0.01298249,0.007536951,0.0009732221],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737357,0.000102744,0.02348279,0.00009946637,0.0001564568,0.00008915421,0.000002362686,0.000004483199,0.002326797],"genre_scores_gemma":[0.927497,0.000004629087,0.07229366,0.0000776648,0.00009259702,6.03985e-9,0.00000106351,0.00001673855,0.00001663785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8266143,"threshold_uncertainty_score":0.8234468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03169787648324553,"score_gpt":0.2135856781911801,"score_spread":0.1818878017079346,"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."}}