{"id":"W2096355787","doi":"10.1002/esp.3780","title":"Digital landscapes of deglaciation: identifying Late Quaternary glacial lake outburst floods using LiDAR","year":2015,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Meltwater; Geology; Deglaciation; Glacial lake; Landform; Geomorphology; Glacial period; Drumlin; Glacier; Digital elevation model; Moraine; Fault scarp; Ice stream; Quaternary; Cryosphere; Oceanography; Paleontology; Remote sensing; Fault (geology); Sea ice","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":[0.0001770214,0.00008298762,0.0000618648,0.002163014,0.0001526978,0.0005013052,0.0001307217,0.000116825,0.001270031],"category_scores_gemma":[0.0004999487,0.00006831217,0.00008163523,0.001100577,0.0001172491,0.0002711466,0.0002990199,0.00006963165,0.00009894164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002611111,"about_ca_system_score_gemma":0.0001001881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01339284,"about_ca_topic_score_gemma":0.03592364,"domain_scores_codex":[0.9999555,0.000009839338,0.000003907706,0.00001002743,0.000009423208,0.00001124113],"domain_scores_gemma":[0.9997564,0.00006852266,0.0000655128,0.00001735506,0.00005195707,0.00004017145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001159919,0.00003996661,0.9459696,0.00004633683,0.00003226299,0.0001856872,0.001154002,0.005662454,0.005952574,0.0003462325,0.0006922553,0.03980261],"study_design_scores_gemma":[0.000004225139,0.00002217001,0.9891664,0.00001024999,0.000008258242,0.00006001187,0.0006324644,0.008863921,0.0003179658,0.00008993552,0.0008207498,0.000003689333],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980732,0.00003079656,0.0003920522,0.00001535134,8.984948e-7,0.000006529857,0.0007002138,0.0000288692,0.0007520753],"genre_scores_gemma":[0.9983807,0.00002201667,0.0008609935,0.000003058624,0.000001535755,0.000005560781,0.0005544064,0.000002598014,0.0001692285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01339284,"threshold_uncertainty_score":0.02662975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01814872452894985,"score_gpt":0.2381732953063813,"score_spread":0.2200245707774315,"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."}}