{"id":"W2014012950","doi":"10.5194/isprsarchives-xxxviii-5-w12-213-2011","title":"THE EFFECTS OF LASER REFLECTION ANGLE ON RADIOMETRIC CORRECTION OF THE AIRBORNE LIDAR INTENSITY DATA","year":2012,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Lidar; Optics; Reflection (computer programming); Intensity (physics); Remote sensing; Ranging; Range (aeronautics); Laser; Geology; Materials science; Physics; Geodesy; 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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.002030806,0.0003369949,0.0003730586,0.000549448,0.001642236,0.0003003399,0.002097996,0.00008939712,0.000005419748],"category_scores_gemma":[0.001846958,0.0001803969,0.0003127223,0.00181997,0.003998144,0.0005001771,0.001436543,0.000461139,0.000004345069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007646474,"about_ca_system_score_gemma":0.0001178551,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6283468,"about_ca_topic_score_gemma":0.08786514,"domain_scores_codex":[0.9955896,0.0004005436,0.001261132,0.0003563313,0.001926029,0.0004663465],"domain_scores_gemma":[0.9948292,0.001922843,0.002007485,0.0009221385,0.000190545,0.0001278396],"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":[0.0001538834,0.00004131732,0.0009826716,0.00002854816,0.00006980825,5.605886e-8,0.002340686,0.00231185,0.004818161,0.000004770905,0.0002084542,0.9890398],"study_design_scores_gemma":[0.0004324133,0.0001443205,0.02946145,0.0002586765,0.00005893435,0.00006957214,0.001043419,0.919838,0.04113082,0.001253969,0.006118729,0.0001897082],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1127156,0.00005197583,0.8633541,0.003489726,0.005249092,0.001098002,0.00008186344,0.00004191293,0.01391778],"genre_scores_gemma":[0.9979105,0.0001669733,0.001061647,0.0005368266,0.0001351301,2.959035e-7,0.00002532441,0.00001065895,0.0001526638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9888501,"threshold_uncertainty_score":0.9996575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804723746380948,"score_gpt":0.2625543182436238,"score_spread":0.2445070807798143,"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."}}