International Space Station: Significant Challenges May Limit Onboard Research
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "In 2010, after about 25 years of work and the expenditure of billions of dollars, the International Space Station (ISS) will be completed. According to the National Aeronautics and Space Administration (NASA), the ISS crew will then be able to redirect its efforts from assembling the station to conducting research. In 2005, Congress designated the ISS as a national laboratory; in addition, the NASA Authorization Act of 2008 required NASA to provide a research management plan for the ISS National Laboratory. In light of these developments, the Government Accountability Office (GAO) was asked to review the research use of the ISS. Specifically, GAO (1) identified how the ISS is being used for research and how it is expected to be used once completed, (2) identified challenges to maximizing ISS research; and (3) identified common management practices at other national laboratories and large science programs that could be applicable to the management of the ISS. To accomplish this, GAO interviewed NASA officials and reviewed key documents related to the ISS. GAO also studied two ground-based national laboratories and several large science institutions."
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 | 0.029 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.025 | 0.012 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
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".