{"id":"W2024251604","doi":"10.1016/j.quaint.2012.01.008","title":"Using LiDAR Digital Elevation Model data to map Lake Agassiz beaches, measure their isostatically-induced gradients, and estimate their ages","year":2012,"lang":"en","type":"article","venue":"Quaternary International","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Core Research for Evolutional Science and Technology; Natural Sciences and Engineering Research Council of Canada","keywords":"Geology; Subaerial; Elevation (ballistics); Digital elevation model; Marine transgression; Lidar; Geomorphology; Extrapolation; Oceanography; Sequence (biology); Sea level; Physical geography; Paleontology; Geography; Remote sensing; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009162322,0.0001976688,0.0001077696,0.001188489,0.0002951369,0.0003583595,0.0002148722,0.0001712141,0.0009556741],"category_scores_gemma":[0.0003222767,0.0001414008,0.0001424563,0.00170955,0.00008862593,0.0003008084,0.0002972962,0.0001553106,0.0004012228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005273829,"about_ca_system_score_gemma":0.0007339039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09019783,"about_ca_topic_score_gemma":0.3642091,"domain_scores_codex":[0.9999273,0.000004131808,0.00000311472,0.00001641778,0.00003228234,0.00001675942],"domain_scores_gemma":[0.9998834,0.000008831898,0.00002978302,0.00001110298,0.0000532466,0.00001350454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000182154,0.0001434657,0.7843407,0.00008105883,0.0001112069,0.0001587282,0.0005596415,0.01260445,0.04056066,0.0004422584,0.0023896,0.1584262],"study_design_scores_gemma":[0.0000369786,0.00005938936,0.9437416,0.00001944907,0.000056247,0.00006011315,0.0004400914,0.04575979,0.00607406,0.000237949,0.003493702,0.00002068003],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984992,0.00007664265,0.006640413,0.0000789223,0.00001139746,0.00004142288,0.003278017,0.0002629241,0.004618257],"genre_scores_gemma":[0.9720532,0.0001025832,0.02235261,0.00001812403,0.00000412808,0.00003704552,0.003498331,0.00001276571,0.001921186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09019783,"threshold_uncertainty_score":0.1793457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1546899531214359,"score_gpt":0.330409453248476,"score_spread":0.1757195001270401,"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."}}