{"id":"W6965296297","doi":"10.3334/ornldaac/2369","title":"ABoVE: Soil Moisture and Active Layer Thickness in Alaska, USA and Canada, 2005-2024","year":2025,"lang":"en","type":"other","venue":"Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Water content; Active layer; Ground-penetrating radar; Moisture; Radar; Synthetic aperture radar; Data logger","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001355698,0.0005216827,0.0004981987,0.0001679101,0.0001079715,0.000052931,0.0002944428,0.000401142,0.0003091249],"category_scores_gemma":[0.0001936768,0.0005318928,0.00007513835,0.0003025647,0.0002980407,0.0001204876,0.0005200724,0.0005658697,0.0000104578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00178115,"about_ca_system_score_gemma":0.000515689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1077495,"about_ca_topic_score_gemma":0.905258,"domain_scores_codex":[0.9976209,0.00007400414,0.000357672,0.0008883618,0.0005155913,0.0005434102],"domain_scores_gemma":[0.9989129,0.0002905685,0.0002538416,0.0002059177,0.00009228736,0.0002444638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004167137,0.000368175,0.1223012,0.000407798,0.0002847373,0.00002708933,0.00004442025,0.0001180059,0.000721292,0.002227573,0.8720742,0.001008855],"study_design_scores_gemma":[0.001751848,0.00003302643,0.07718161,0.0003538512,0.00008387653,0.00001093249,0.0001442095,0.008257753,0.000277882,0.002143383,0.9088458,0.0009157571],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01719649,0.00005630929,0.0001911547,0.000558836,0.0002831629,0.0007296522,0.9572104,0.00002942422,0.02374454],"genre_scores_gemma":[0.02942804,0.0004099236,0.0009305635,0.001253735,0.0003335083,0.0003842001,0.9544495,0.0003812003,0.01242935],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7975085,"threshold_uncertainty_score":0.9997132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003447370063658122,"score_gpt":0.20867754283751,"score_spread":0.2052301727738519,"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."}}