SpectroGrid: Providing Simple Secure Remote Access to Scientific Instruments
Bibliographic record
Abstract
With the availability of high performance networks and the increase in the number of online scientific instruments, remote instrumentation is a topic with much popularity lately, promising better instrument utilization, easier collaboration between distant organizations and diminution of travel-related costs and overhead. At NRC we needed a simple and secure method for researchers to remotely access nuclear magnetic resonance (NMR) instruments located at the National Ultrahigh-Field NMR Facility for Solids for data acquisition and visualization purposes. This paper discusses the design and implementation of SpectroGrid: a simple remote instrumentation solution based on open source technologies. VNC (virtual network computing) is used as the remote control implementation, and security is provided by the grid security infrastructure (GSI) and secure shell (SSH). A discussion about the cost-saving potentials of SpectroGrid for the Canadian research community will also be given. SpectroGrid is currently being used by Canadian researchers to remotely access NMR instruments located at NRC in Ottawa.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.012 |
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".