Data and and code for "Validation and uncertainty quantification of three state-of-the-art ammonia surface exchange schemes using NH3 flux measurements in a dune ecosystem"
Bibliographic record
Abstract
The data and code presented here are associated with the study "Validation and uncertainty quantification of three state-of-the-art ammonia surface exchange schemes using NH3 flux measurements in a dune ecosystem" by Jongenelen et al. (2025). This repository includes the file jongenelenetal2025.7z , which contains the following directories: figure_scripts: Contains the scripts to make the figures. figures: Map to which the figures will be exported. model_output: Contains the model output, which is loaded in the scripts. sensivity_analysis_output: Contains the output of the sensitivity analysis per variable per scheme. uncertainty_analysis_output: Contains the output of the uncertainty analysis, which is used as input for fig A1. Running the Scripts To execute the scripts in figure_scripts directory, ensure that the directory_name variable is set to the absolute path of your `/figure_scripts/` directory. For example: directory_name = "/path/to/your/project/figure_scripts/" Solleveld Data The Solleveld dataset used in this study is available in a separate repository:https://zenodo.org/records/14936840 (doi: https://doi.org/10.21945/566085a2-a00f-4e0a-833d-3fcf975027d2)
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.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.120 | 0.082 |
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".