Bibliographic record
Abstract
Your discussion of the challenges facing the International Council for Science paints a misleadingly negative picture (Nature 515, 311; 2014).We are a non-governmental organization representing academies and research councils from 140 countries and the science community through 31 disciplinary unions, and are a leading voice for science.The council has initiated global research projects such as the International Polar Years.Our current flagship projects are Future Earth: Research for Global Sustainability; Urban Health and Wellbeing; and Integrated Research on Disaster Risk.The biological sciences are fully integrated into our programmes (see go.nature.com/xhzhif).The council represents science in global organizations such as the United Nations Educational, Scientific and Cultural Organization, and is the scientific and technology lead for the UN sustainable development goals programme.The council is dedicated to the promotion of freedom and responsibility of scientists, and champions open access to data and information through its Committee on Data for Science and Technology and new World Data System.To improve links between science and policy, the council convened a meeting of governmental science advisers (www.globalscienceadvice.org), and a global network is being established.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
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; both teacher heads 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".