{"id":"W4400365050","doi":"10.3390/rs16132461","title":"Drone-Based Ground-Penetrating Radar with Manual Transects for Improved Field Surveys of Buried Ice","year":2024,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; École de Technologie Supérieure","funders":"Natural Resources Canada; Parks Canada; Ohio State University; Natural Sciences and Engineering Research Council of Canada; Arctic Institute of North America","keywords":"Ground-penetrating radar; Geology; Transect; Drone; Glacier; Terrain; Debris; Remote sensing; Radar; Geomorphology; Geography; Oceanography; Cartography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037422,0.0001107904,0.0001600318,0.00002420116,0.0001636079,0.00005681394,0.00004931543,0.00004448873,0.00003299345],"category_scores_gemma":[0.0000402147,0.00008755773,0.00006202453,0.0002312567,0.00003524259,0.00007604971,0.000002375625,0.00008517619,0.000001693036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004739499,"about_ca_system_score_gemma":0.00007478866,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006875637,"about_ca_topic_score_gemma":0.01059768,"domain_scores_codex":[0.9992332,0.00005002547,0.0001834697,0.0002089557,0.0001123211,0.0002120165],"domain_scores_gemma":[0.9989292,0.0008245332,0.00004403006,0.0001091073,0.00005259107,0.00004051573],"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":[0.0001522241,0.000007992718,0.0009339395,0.0004481684,0.000125405,0.00002531514,0.001027539,0.00219456,0.009192245,0.00002000861,0.000209348,0.9856632],"study_design_scores_gemma":[0.0005310089,0.0005290259,0.03435105,0.0002695124,0.00007515884,0.00001284715,0.0006130676,0.9585949,0.002239112,0.0002150269,0.002314931,0.0002543708],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7863587,0.0007159224,0.210903,0.0007640983,0.0003265316,0.0002734713,0.00004059466,0.00006413365,0.0005535554],"genre_scores_gemma":[0.9465501,0.00001283048,0.0529403,0.0001849235,0.0001473916,1.2253e-8,0.00006582278,0.000006991148,0.00009167859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9854089,"threshold_uncertainty_score":0.9997377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063617488936028,"score_gpt":0.2391202865053983,"score_spread":0.2184841116160381,"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."}}