Remote Internet Access to Advanced Analytical Facilities: A New Approach with Web-Based Services
Bibliographic record
Abstract
Over the past decade, the increasing availability of the World Wide Web has held out the possibility that the efficiency of scientific measurements could be enhanced in cases where experiments were being conducted at distant facilities. Examples of early successes have included X-ray diffraction (XRD) experimental measurements of protein crystal structures at synchrotrons and access to scanning electron microscopy (SEM) and NMR facilities by users from institutions that do not possess such advanced capabilities. Experimental control, visual contact, and receipt of results has used some form of X forwarding and/or VNC (virtual network computing) software that transfers the screen image of a server at the experimental site to that of the users' home site. A more recent development is a web services platform called Science Studio that provides teams of scientists with secure links to experiments at one or more advanced research facilities. The software provides a widely distributed team with a set of controls and screens to operate, observe, and record essential parts of the experiment. As well, Science Studio provides high speed network access to computing resources to process the large data sets that are often involved in complex experiments. The simple web browser and the rapid transfer of experimental data to a processing site allow efficient use of the facility and assist decision making during the acquisition of the experimental results. The software provides users with a comprehensive overview and record of all parts of the experimental process. A prototype network is described involving X-ray beamlines at two different synchrotrons and an SEM facility. An online parallel processing facility has been developed that analyzes the data in near-real time using stream processing. Science Studio and can be expanded to include many other analytical applications, providing teams of users with rapid access to processed results along with the means for detailed discussion of their significance.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.012 | 0.024 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".