{"id":"W2402318270","doi":"10.14358/pers.82.5.351","title":"ICESat/GLAS Canopy Height Sensitivity Inferred from Airborne Lidar","year":2016,"lang":"en","type":"article","venue":"Photogrammetric Engineering & Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"Australian National Botanic Gardens","keywords":"Remote sensing; Lidar; Point cloud; Percentile; Environmental science; Altimeter; Canopy; Raster graphics; Laser scanning; Meteorology; Geography; Laser; Mathematics; Statistics; Optics; Physics; Engineering; 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":[0.002039942,0.0003195818,0.0002352659,0.0007985587,0.0002968923,0.0006198268,0.0003802911,0.0002592134,0.0006803128],"category_scores_gemma":[0.005419513,0.0002453246,0.0002191382,0.000901284,0.0002427924,0.0005062487,0.0004887629,0.000218813,0.0001839567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007320655,"about_ca_system_score_gemma":0.000351486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01266139,"about_ca_topic_score_gemma":0.02024299,"domain_scores_codex":[0.9989845,0.0002893807,0.00007515329,0.0002088089,0.0003315485,0.0001105758],"domain_scores_gemma":[0.9977912,0.00131532,0.0002344743,0.0002752219,0.0003492964,0.00003445538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008572881,0.0001195287,0.7348361,0.0002558236,0.0003136954,0.0004193081,0.0007120743,0.1340318,0.06625997,0.001241688,0.001866102,0.05908661],"study_design_scores_gemma":[0.00004345435,0.0001493361,0.8317199,0.00004708624,0.0001525178,0.0002817716,0.0004339716,0.1268976,0.03660849,0.001006592,0.00260457,0.00005483231],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903657,0.00009231151,0.005678205,0.00003749279,0.00001029967,0.00002358092,0.001153744,0.0001685572,0.00247006],"genre_scores_gemma":[0.9933031,0.00003529316,0.005296941,0.0000484658,0.000004177134,0.00001244989,0.001122628,0.00003862346,0.0001384241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01266139,"threshold_uncertainty_score":0.02517539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008689661699295446,"score_gpt":0.204992934926042,"score_spread":0.1963032732267465,"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."}}