{"id":"W2618959650","doi":"","title":"Unmanned Aerial Vehicle Remote Sensing of Shallow Snow: Assessment and Possibilities for Improved Snow Depletion Prediction","year":2015,"lang":"en","type":"article","venue":"2015 AGU Fall Meeting","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Snow; Remote sensing; Environmental science; Meteorology; Geology; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006894168,0.0001094206,0.0001852911,0.00002230456,0.0001926236,0.00004796447,0.00005661785,0.00006051984,0.000006023839],"category_scores_gemma":[0.000401127,0.00009701231,0.00004189708,0.00009319273,0.00005765502,0.0001502111,0.00002093559,0.00006095882,0.000001423379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001810919,"about_ca_system_score_gemma":0.0000678001,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01457042,"about_ca_topic_score_gemma":0.02132617,"domain_scores_codex":[0.9990592,0.00005213139,0.0002906206,0.0002231978,0.0001562665,0.0002185743],"domain_scores_gemma":[0.9991753,0.000270771,0.0001504754,0.000119818,0.0001948177,0.00008885702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004098157,0.00003168196,0.8010106,0.0001341687,0.0001096522,0.000001615281,0.003527295,0.004759755,0.002279016,0.00005429962,0.003029509,0.1846526],"study_design_scores_gemma":[0.001010532,0.0003788914,0.3712868,0.00009237291,0.00004247527,0.000002956087,0.003529576,0.6207463,0.0000898641,0.001125509,0.001549111,0.0001456187],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992964,0.0003692997,0.00441325,0.0004552679,0.0006303171,0.0003366524,0.00008589285,0.00004546382,0.0006998574],"genre_scores_gemma":[0.9618792,0.00005004481,0.03741337,0.00006800317,0.0003397507,6.743311e-7,0.0001270786,0.000006109556,0.0001157864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6159865,"threshold_uncertainty_score":0.9965321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03606358190955056,"score_gpt":0.2657672847984154,"score_spread":0.2297037028888648,"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."}}