PK-4 - Complex Plasma Research on the International Space Station
Bibliographic record
Abstract
The International Space Station (ISS) is the outpost of mankind in low-Earth orbit, and has been permanently manned by three to six astronauts since the end of 2000. It is the world’s biggest international project yet, bringing together partners from Russia, America, Europe, Japan and Canada. It was built following a political decision after the Cold War and provides a platform for fundamental research in life and physical sciences, for Earth observation and astronomy. Recently it became the platform for preparing the next steps in the quest for longer deep-space manned missions to the Moon and Mars. PK-4 is an active laboratory for fundamental research in the field of complex plasmas and part of the European Columbus Module. The project is a bilateral European-Russian collaboration. Scientists from Europe, Russia and also other nations worldwide benefit from this project. They participate in experiments, the analysis of resulting data and contribute to theoretical and numerical modelling. Experiments with PK-4 are carried out in frequent campaigns on the ISS. In 2019 three such campaigns totalling 12 experiment days were performed, producing about 9 TB of high quality scientific data.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".