Set up and Guiding Principles of the Netherlands National Open Science Festival 2020- 2023
Bibliographic record
Abstract
This document describes the Setup and Guiding Principles for the first three editions of the Netherlands National Open Science Festival: 2020 at the Wageningen University and Research (due to Covid this edition was canceled and changed to an online Festival in 2021), 2022 at the Vrije Universiteit in Amsterdam, 2023 at the Erasmus University Rotterdam. Also see the Guidelines for Community Led Sessions at the Netherlands National Open Science Festival (online) that were previously shared, and the following collections of outputs of the Festival: A Collection of Open Science Use Cases A Collection of Open Science Use Cases on Societal Engagement https://zenodo.org/communities/osf2021nl/ https://zenodo.org/communities/osf2022nl/ https://zenodo.org/communities/osf2023nl/
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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 | 0.082 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.029 | 0.011 |
| Open science | 0.006 | 0.021 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.025 | 0.021 |
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".