{"id":"W2009632224","doi":"10.1002/hyp.8167","title":"Investigating the spatial distribution of water levels in the Mackenzie Delta using airborne LiDAR","year":2011,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Geological Survey of Canada; Natural Resources Canada; Environment and Climate Change Canada; Acadia University","funders":"National Health Research Institutes; ArcticNet; Aurora Research Institute","keywords":"Lidar; Delta; Hydrology (agriculture); Hydraulics; Channel (broadcasting); Geology; Hydraulic head; River delta; Environmental science; Geomorphology; Remote sensing; 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":[0.0003995522,0.00008440233,0.00008892595,0.000007049053,0.0001695719,0.00001388022,0.0002861189,0.00005754117,0.0001519592],"category_scores_gemma":[0.0001754253,0.00003632793,0.00002339957,0.0002296107,0.000500721,0.00006595937,0.00009621487,0.0001406754,0.00002516538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002017215,"about_ca_system_score_gemma":0.000009813421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002327569,"about_ca_topic_score_gemma":0.0003094379,"domain_scores_codex":[0.9991696,0.00009501495,0.0001966001,0.0001751549,0.0001737101,0.0001899151],"domain_scores_gemma":[0.9996339,0.00008119945,0.00006462028,0.0001820706,0.00001263782,0.00002558499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002231227,0.003102388,0.4733498,0.0004554877,0.00009547915,0.00006641756,0.08518524,0.0413429,0.2947401,0.003629558,0.001327916,0.09648156],"study_design_scores_gemma":[0.0003437581,0.0002131128,0.7681518,0.00004387106,0.00005329544,0.00005794593,0.0005749073,0.02312116,0.1615334,0.04320329,0.002369711,0.0003337711],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948424,0.00001743722,0.003104478,0.0005140671,0.00001165808,0.000155666,0.0000104763,0.00001643288,0.001327359],"genre_scores_gemma":[0.9991856,0.000002811176,0.0004847078,0.0002728955,0.00002281323,0.000004286689,0.00001906575,0.00000389873,0.000003894635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.294802,"threshold_uncertainty_score":0.3518604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06120011205559547,"score_gpt":0.2559468020527657,"score_spread":0.1947466899971702,"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."}}