Benchmarking ray-traced tropospheric delays
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Benchmarking ray-traced tropospheric delays Vahab Nafisi(1,2,3), Landon Urquhart(5), Marcelo C. Santos(5), Felipe G. Nievinski(8), Johannes Bohm(1), Dudy D. Wijaya(1), Harald Schuh(1), Alireza A. Ardalan(2) ,Thomas Hobiger(4), Ryuichi Ichikawa(4), Florian Zus(6), Jens Wickert(6), Pascal Gegout(7) (1) Institute of Geodesy and Geophysics, Vienna University of Technology, Austria,(2) Department of Surveying and Geomatics Engineering, College of Engineering, University of Tehran, Iran (3) Department of Surveying Engineering, Faculty of Engineering, University of Isfahan, Iran,(4) Space-Time Standards Group, Kashima Space Research Center, National Institute of Information and Communication Technology, Kashima, Japan,(5) Department of Geodesy and Geomatics Engineering, University of New Brunswick, Canada,(6) German Research Centre for Geosciences GFZ, Sect. 1.1 GPS/Galileo Earth Observation, Potsdam, Germany ,(7) Groupe de Recherche de Geodesie Spatiale – Toulouse, France,(8) Department of Aerospace Engineering Sciences, University of Colorado at Boulder, USA. Email : vahab.nafisi@tuwien.ac.at
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it