Commitment to Advance Excellence and Inclusion in the Earth and Space Sciences Scholarly Publications
Bibliographic record
Abstract
Abstract Addressing global challenges and advancing knowledge in the Earth and space sciences requires an equitable, diverse, and inclusive scholarly community where researchers must be freely able to conduct, collaborate on, share, review, and discuss their research on important economic and societal topics such as climate change. The current Executive Orders in the United States focus on censoring research and researchers by banning specific words, removing access to data sets, or by restricting what type of research can be funded or published, therefore compromising the knowledge that researchers are able to produce. As Editors‐in‐Chief of AGU publications we stand by our mission to support the publication of evidence‐based, rigorously vetted research without political pressure. Collectively, our peer‐reviewed journals and books provide inclusive publication outlets for the global research community to advance Earth and space sciences and to strengthen the public's trust in scientific evidence.
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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 | 0.234 | 0.508 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.013 | 0.019 |
| Scholarly communication | 0.090 | 0.035 |
| Open science | 0.006 | 0.052 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.032 | 0.032 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".