{"id":"W4225533213","doi":"10.1109/lgrs.2022.3166665","title":"Evaluation of LiDAR-Derived Snow Depth Estimates From the iPhone 12 Pro","year":2022,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Lidar; Snow; Mean squared error; Remote sensing; Computer science; Mathematics; Environmental science; Algorithm; Meteorology; Statistics; Physics; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009265315,0.00008930739,0.0001134231,0.00001875929,0.0009442517,0.00004847745,0.0001410003,0.00001384175,0.00009275591],"category_scores_gemma":[0.0001429071,0.00006123643,0.00003312096,0.0002881048,0.000277534,0.00008983567,0.00002709493,0.0001055889,0.000003168518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001007265,"about_ca_system_score_gemma":0.0000595326,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01966157,"about_ca_topic_score_gemma":0.004824298,"domain_scores_codex":[0.9985939,0.0001271736,0.000154305,0.0002376752,0.0006871471,0.0001998123],"domain_scores_gemma":[0.9993225,0.0003146329,0.0001050328,0.0001637708,0.0000589907,0.00003509258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001689353,0.000007354795,0.02864693,0.000003869782,0.00003114685,0.000005961851,0.003283876,0.01921254,0.0170929,5.821286e-7,0.001337196,0.9303607],"study_design_scores_gemma":[0.0001669981,0.00003548422,0.6052384,0.0000152765,0.00005676276,0.000009501588,0.001291989,0.3917138,0.0004422968,0.000222672,0.0007140312,0.00009283397],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910487,0.0005009255,0.002950598,0.004371229,0.0007821842,0.0001856273,0.00002635558,0.00001690096,0.000117498],"genre_scores_gemma":[0.9891196,0.00004577122,0.008440757,0.002268203,0.00008730918,1.090301e-7,0.00001948895,0.000002399528,0.00001630849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9302679,"threshold_uncertainty_score":0.9868666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04587030457849842,"score_gpt":0.2444853582816628,"score_spread":0.1986150537031644,"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."}}