{"id":"W322303216","doi":"10.1007/978-3-662-04709-5_35","title":"Improving DGPS Accelerations for Airborne Gravimetry: GPS Carrier Phase Accelerations Revisited","year":2002,"lang":"en","type":"book-chapter","venue":"International Association of Geodesy symposia","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Gravimetry; Global Positioning System; Acceleration; Geodesy; Gravitational field; Accelerometer; Gravitational acceleration; Covariance; Remote sensing; Computer science; Aerospace engineering; Geology; Engineering; Physics; Mathematics; Telecommunications; Optics; Interferometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003179148,0.001862032,0.001375579,0.001427664,0.0004758076,0.003239024,0.002021263,0.002533906,0.005086944],"category_scores_gemma":[0.01058646,0.001106106,0.0006404701,0.004972306,0.001255392,0.004667348,0.001377041,0.003736173,0.004619077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107628,"about_ca_system_score_gemma":0.001687543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009353354,"about_ca_topic_score_gemma":0.01430958,"domain_scores_codex":[0.9983912,0.0003896265,0.0001105495,0.0002282913,0.0007940287,0.00008618422],"domain_scores_gemma":[0.9959587,0.001422822,0.0001453838,0.0007931775,0.00162196,0.00005790739],"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":[0.0001028828,0.00003864657,0.001498771,0.0004574914,0.0000755704,0.00006345406,0.0001900164,0.02045231,0.006748115,0.1151984,0.05491149,0.8002627],"study_design_scores_gemma":[0.0001027968,0.0003175919,0.0119281,0.001086632,0.0003290396,0.001058623,0.0005116584,0.1613242,0.02331738,0.2313381,0.5684436,0.0002422882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0231762,0.1104225,0.7299379,0.04121143,0.009939321,0.00007504128,0.001186514,0.004209013,0.079842],"genre_scores_gemma":[0.2994515,0.1168361,0.5007442,0.006425047,0.009824554,0.00009706945,0.001395387,0.002456739,0.06276943],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009353354,"threshold_uncertainty_score":0.01859778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02919816410340642,"score_gpt":0.2551877073417415,"score_spread":0.2259895432383351,"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."}}