{"id":"W4415849494","doi":"10.5194/essd-17-5833-2025","title":"Monitoring the Earth's deformation with the SPOTGINS series","year":2025,"lang":"en","type":"article","venue":"Earth system science data","topic":"GNSS positioning and interference","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Aerospace Exploration Agency; University of California, San Diego; National Oceanic and Atmospheric Administration; Kartverket; Vlaamse regering; Institut de Physique du Globe de Paris; Wuhan University; Regione Campania; Natural Environment Research Council; Istituto Nazionale di Geofisica e Vulcanologia; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche; Universidad Politécnica de Madrid; Natural Resources Canada; Korea Astronomy and Space Science Institute; European Space Agency; Universidade da Beira Interior; Centre National d’Etudes Spatiales; University of Hawai'i","keywords":"Series (stratigraphy); Geodetic datum; Time series; Satellite; Range (aeronautics); Product (mathematics); Deformation monitoring; Software","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005927634,0.00007422141,0.00006032434,0.00004988954,0.0005575605,0.0003658669,0.001052351,0.00001442661,0.00000211245],"category_scores_gemma":[0.00002085037,0.0000369359,0.000007755947,0.0005404736,0.0001891205,0.001007457,0.0001416184,0.0001088857,0.00005361728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001917905,"about_ca_system_score_gemma":0.00005539666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003388839,"about_ca_topic_score_gemma":0.00003542532,"domain_scores_codex":[0.9993102,0.00001997099,0.0001072548,0.0001442819,0.0002333635,0.0001849268],"domain_scores_gemma":[0.999037,0.00002958566,0.00002258762,0.0008349025,0.00005269747,0.00002324214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001714684,0.0001181234,0.06160156,0.003421919,0.0005559987,0.00003942842,0.03882611,0.3517672,0.1047495,0.2406788,0.03806184,0.1600082],"study_design_scores_gemma":[0.0004123936,0.000126342,0.2382246,0.003476602,0.00007314473,0.000245916,0.02440396,0.5745454,0.1033986,0.00003700074,0.0544435,0.0006124395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.911285,0.0005162932,0.02898945,0.001151448,0.002455951,0.0004911947,0.0001151296,0.0006571948,0.05433827],"genre_scores_gemma":[0.9993698,0.000007506604,0.0002684643,0.00001248157,0.00005357803,0.00001039108,0.000007712497,0.000003468619,0.0002665856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2406418,"threshold_uncertainty_score":0.4288361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01593989892143013,"score_gpt":0.2267193112187392,"score_spread":0.2107794122973091,"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."}}