{"id":"W4399824911","doi":"10.1002/wsb.1532","title":"Using the full potential of Airborne Laser Scanning (aerial LiDAR) in wildlife research","year":2024,"lang":"en","type":"article","venue":"Wildlife Society Bulletin","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lidar; Aerial survey; Wildlife; Laser scanning; Remote sensing; Environmental science; Geography; Wildlife management; Ecology; Laser; Biology; Optics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001891159,0.0001537718,0.0001772651,0.00004043775,0.0003575412,0.0001148977,0.0003495181,0.0001426664,0.000823967],"category_scores_gemma":[0.00007244871,0.0001222497,0.0002098355,0.000863091,0.0007754081,0.00005747931,0.0003089729,0.0006173819,0.0004046374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002255833,"about_ca_system_score_gemma":0.00007472499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00196219,"about_ca_topic_score_gemma":0.00004016983,"domain_scores_codex":[0.9977599,0.0002357029,0.0003556952,0.0004577724,0.0007145156,0.0004763856],"domain_scores_gemma":[0.9992281,0.0001904439,0.0000568039,0.0004117294,0.00002561786,0.00008725715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009010518,0.0002451272,0.002977546,0.00009642942,0.00009498617,0.0000326404,0.009321046,0.03603632,0.06533834,0.0003528473,0.8754616,0.00995298],"study_design_scores_gemma":[0.0007614812,0.000114426,0.01276587,0.0003934233,0.00006151666,0.0000626554,0.00617173,0.0787937,0.001836021,0.0007479441,0.8977638,0.0005273939],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693782,0.0001854273,0.001739169,0.02419102,0.000307777,0.0003979342,0.00001252849,0.00007886146,0.003709016],"genre_scores_gemma":[0.9908175,0.00005996778,0.007046093,0.0008558452,0.0004234946,0.000006698051,0.000006836027,0.00003735988,0.0007462208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06350231,"threshold_uncertainty_score":0.9021862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03141508422435994,"score_gpt":0.3040360693105041,"score_spread":0.2726209850861441,"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."}}