{"id":"W2163450348","doi":"10.1002/2014gl061307","title":"Removal of systematic seasonal atmospheric signal from interferometric synthetic aperture radar ground deformation time series","year":2014,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Natural Resources Canada","funders":"","keywords":"Radiosonde; Interferometric synthetic aperture radar; Subsidence; Geology; Geodesy; Troposphere; Synthetic aperture radar; Interferometry; Deformation (meteorology); Levelling; Geodetic datum; Amplitude; Series (stratigraphy); Remote sensing; Atmospheric sciences; Geomorphology; Optics; Physics","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":[0.0005591253,0.0002313463,0.000492163,0.0001015605,0.0001169007,0.00007962351,0.0004787562,0.0001168256,0.0001335069],"category_scores_gemma":[0.0003562998,0.0001902045,0.0001485299,0.000897371,0.0002342106,0.0002329655,0.00009437651,0.0004327961,0.0003195388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001719443,"about_ca_system_score_gemma":0.00001937328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008139095,"about_ca_topic_score_gemma":0.000001242619,"domain_scores_codex":[0.9976702,0.0002685606,0.0004130423,0.0002811933,0.0009177793,0.0004492379],"domain_scores_gemma":[0.9973177,0.001799928,0.0000673601,0.0005552495,0.0001243142,0.0001354449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002411184,0.000540138,0.00003706582,0.01422706,0.0008683224,0.00006936472,0.001485568,0.0001461866,0.6692747,0.0177044,0.009746558,0.2856595],"study_design_scores_gemma":[0.001566576,0.0011074,0.003445262,0.008620138,0.0003596451,0.0002881247,0.0007525967,0.7873379,0.05903142,0.02182075,0.1132996,0.002370662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4487707,0.0005428204,0.54453,0.00154668,0.0001079606,0.001085489,0.000052069,0.0005375958,0.002826606],"genre_scores_gemma":[0.926424,0.00002546344,0.07296548,0.0001037571,0.000194307,0.0001054592,0.0000423109,0.0000555741,0.00008368794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7871917,"threshold_uncertainty_score":0.7756314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191853809209984,"score_gpt":0.2369702937260389,"score_spread":0.225051755633939,"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."}}