Benchmarking ray-traced tropospheric delays
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".