IPY 2007–2008 data legacy – a long story cut short
Bibliographic record
Abstract
Abstract. The International Polar Year 2007–2008 was a synchronized effort to simultaneously collect data from polar regions. Being the fourth in a row of IPYs, the demand for interdisciplinarity and new data products was high. However, despite of all the research done on land, people, ocean, ice and atmosphere and the large amount of data collected, no central archive or portal was created for IPY data. In order to address these issues, a concerted effort between PANGAEA – Data Publisher for Earth and Environmental Science, the ICSU World Data System (WDS), and the International Council for Scientific and Technical Information (ICSTI) was undertaken to extract data resulting from IPY publications for long-term preservation. 1380 IPY-related references were collected. Out of these, only 450 contained accessible data. All data was extracted, quality checked, annotated with metadata and uploaded to PANGAEA. The 450 articles dealt with a multitude of IPY topics – plankton biomass, water chemistry, ice thickness, whale sightings, Inuit health, alien species introductions by travelers or tundra biomass change – to mention just a few. Both, the Arctic and the Antarctic were investigated in the articles, and all realms (land, people, ocean, ice and atmosphere) and a wide range of countries were covered. The data compilation can now be found with the identifier doi:10.1594/PANGAEA.150150 and individually searched for using the PANGAEA search engine (www.pangaea.de) and adding "+project:ipy". With this effort, we hope to improve the visibility, accessibility and long-term storage of IPY data for future research and new data products.
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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.024 | 0.041 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.040 |
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".