2025 WDS Members Forum: North & South America Regional Session
Bibliographic record
Abstract
The World Data System's 2025 Members Forum was divided into three regional webinars targeting Asia and Oceania, Europe and Africa, and North and South America. These sessions highlighted the 2025-2027 Action Plan, presented by Dr. David Castle, outcomes from the work developed by the Subcommittee on Standards and Certifications, presented by Daniela Santos Oliveira, and results from the Data Repository Investment Value and Relevance (DRIVR) project, presented by Reyna Broadhurst. This session included the following member reports, both presented live and video recordings. National Center for Atmospheric Research Ocean Networks Canada Worldwide Protein Data Bank The webinar ended with highlighting the 2025 WDS Data Stewardship Award winners and a video presentation from 1st place winner Dr. Youhua Ran. A recording of the entire session can be found here.
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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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.245 | 0.101 |
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".