New digital developments for <scp>RGS</scp>‐<scp>IBG</scp> journals in 2018
Bibliographic record
Abstract
We are very pleased to announce that the Royal Geographical Society (with IBG) has partnered with Wiley to deliver a digital-first publishing approach – hence the new look for the journals and papers. This will help make the submission process more straightforward, improve article design so that papers are easier to read online, and enable faster production times. The digital-first approach involves greater standardisation of article formatting and will, in the future, allow us to publish papers that integrate text, images, data, multimedia, and code. Information for submitting authors is available on each of the journal's websites. The updated author guidelines also include guidance about Data Accessibility Statements, which describe the location and accessibility of the data that underpins articles and can be included at the point of submission (on an optional basis), and ORCID iDs, which will be required for submitting authors from January 2018. Wiley are also launching a new Society publications website in 2018. This will include: all RGS-IBG journals (Area, The Geographical Journal, Transactions of the Institute of British Geographers, Geo: Geography and Environment and WIRES Climate Change); the RGS-IBG Book Series; Geography Directions and the Geo blog; and other resources such as the Society's publishing guide. A new guide about Open Data will be published in 2018. Linked to development of the new Wiley websites, and the Society's new website, the journal covers have been re-designed in RGS-IBG colours. The new Wiley websites will enhance the searchability and discoverability of research published in Society titles and allow content on specific topics to be accessed with greater ease.
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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.024 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.321 | 0.311 |
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".