Cost-effective approach to quality assurance via failure modes and effects analysis for the development of GIRMOS for the Gemini North Telescope
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Gemini Infra-Red Multi-Object Spectrograph (GIRMOS) is a high-resolution integral-field spectroscope and imager being built by a consortium of Canadian universities and institutions, along with the International Gemini Observatory (Gemini) and the Korea Astronomy and Space Science Institute (KASI). The team needed a cost-effective way to bring a degree in Product and Quality Assurance to bear on instrument development, but without availability of a dedicated team. Advice and support from the Thirty Meter Telescope (TMT) Systems Engineering Team enabled GIRMOS to tailor and scale the TMT approach to fit within the available resources of a much smaller project. This Failure Modes and Effects Analysis (FMEA) method more easily allowed geographically distributed subsystem teams to work independently within an agreed-upon FMEA framework that rolled up into a System-level analysis. The TMT FMEA framework reduced the effort involved in all the follow-on work that used the same data set, namely sparing analysis, reliability and uptime analyses, and accelerated life testing.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it