Bibliographic record
Abstract
Maryland from October 3 1 through November 3,1994, was hosted by the Institute of Environmental Sciences (IES) and was supported by the American Institute of Aeronautics and Astronautics (AIAA), the American Society for Testing and Materials (ASTM), the National Aeronautics and Space Administration (NASA), and the Canadian Space Agency (CSA). These proceedings attest to the breadth of the conference; papers were presented on topics as diverse as materials degredation in low Earth orbit, the Martian environment and several aspects of the still commercially dominant geostationary orbit. A good cross section of the space flight community took advantage of the opportunity to get together, to share their experiences and to participate in the sessions addressed by three invited speakers. Frank Cepollina covered the Hubble Space Telescope (HST) Servicing Mission; Paul Regeon of Clementine Program fame- the role of testing in the Deep Space Program Science Experiment and Alexander Makarov of the Russian Space Agency- the facilities and capabilities of the NIICHIMMASH Organization. Tours of NASA Goddard Space
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.241 | 0.181 |
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".