Small science and big science entanglement: the advent of a new era of synchrotron light sources for chemical research—Chemistry at the Edge
Bibliographic record
Abstract
Large facilities (big science) that provide advanced capabilities not available in researchers’ laboratories in universities and institutions have become increasingly indipensible to advance research and innovation. A synchrotron light source is one of such facilities crucial to chemical research. Herein, the entanglement of small science and big science in general is described with emphasis placed on the interplay of research in individuals’ laboratory (small science), and advanced tools at the synchrotron light source (big science) from the perspective of matching scientific problems with techniques at the synchrotron for solution, and the interaction of users with the staff and management of the facility (human activity). The discussion is focused on one phenomenon, X-ray absorption and related techniques, which are element specific and ideally suited for probing structure and bonding of materials and their functionality. I will describe why X-ray absorption spectroscopy is literally “Chemistry at the Edge”. The sociology of synchrotron research and its impact on science will also be presented. The evolution of synchrotron science and technology globally will be noted, especially the history of R&D of synchrotron research in Canada and the bright prospect for chemical research using future synchrotron light sources.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.044 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".