{"id":"W3011806917","doi":"10.3390/rs12060967","title":"Improving the Estimation of Water Level over Freshwater Ice Cover using Altimetry Satellite Active and Passive Observations","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Environment and Climate Change Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs; Centre National d’Etudes Spatiales","keywords":"Altimeter; Remote sensing; Water level; Satellite; Environmental science; Brightness temperature; Geology; Brightness; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00006347821,0.0001047242,0.0001397819,0.00001412006,0.0003129746,0.00004843952,0.00004987384,0.00004024761,0.00008151709],"category_scores_gemma":[0.00009372692,0.00006431805,0.00003804627,0.0001707693,0.00007886774,0.0002153621,0.00003054122,0.0001001254,0.000008996107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007133455,"about_ca_system_score_gemma":0.00001985543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004433818,"about_ca_topic_score_gemma":0.0006354088,"domain_scores_codex":[0.9992604,0.00004003788,0.0001924767,0.0001760492,0.0001528454,0.0001782065],"domain_scores_gemma":[0.9995121,0.0001732298,0.00009461927,0.0001023699,0.00006906159,0.00004860063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007401864,0.000005024474,0.0108163,0.00008534143,0.0001276135,0.000009597649,0.008726328,0.104754,0.03703745,0.0000124745,0.0001357939,0.8382161],"study_design_scores_gemma":[0.0001226701,0.00001807417,0.09369292,0.00001934439,0.0000427358,0.00000416515,0.0005173282,0.90011,0.004429453,0.00008126427,0.0008707555,0.00009125579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9661561,0.0001608137,0.0321718,0.001120684,0.0001007898,0.000143702,0.00005285342,0.00001621752,0.00007705032],"genre_scores_gemma":[0.9531015,0.00003988003,0.04576893,0.0009187844,0.00009366506,4.553622e-9,0.00004645112,0.000005229323,0.00002553719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8381249,"threshold_uncertainty_score":0.6702636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05701865417899978,"score_gpt":0.2351456550690455,"score_spread":0.1781270008900457,"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."}}