Mercury Free Microscopy: An Opportunity for Core Facility Directors
Bibliographic record
Abstract
Mercury Free Microscopy (MFM) is a new movement that encourages microscope owners to choose modern mercury free light sources to replace more traditional mercury based arc lamps. Microscope performance is enhanced with new solid state technologies because they offer a more stable light intensity output and have a more uniform light output across the visible spectrum. Solid state sources not only eliminate mercury but also eliminate the cost of consumable bulbs (lifetime ∼200 hours), use less energy, reduce the instrument down time when bulbs fail and reduce the staff time required to replace and align bulbs. With lifetimes on the order of tens of thousands of hours, solid state replacements can pay for themselves over their lifetime with the omission of consumable, staff (no need to replace and align bulbs) and energy costs. Solid state sources are also sustainable and comply with institutional and government body mandates to reduce energy consumption, carbon footprints and hazardous waste. MFM can be used as a mechanism to access institutional financial resources for sustainable technology through a variety of stakeholders to defray the cost to microscope owners for the initial purchase of solid state sources or the replacement cost of mercury based sources. Core facility managers can take a lead in this area as "green" ambassadors for their institution by championing a local MFM program that will save their institution money and energy and eliminate mercury from the waste stream. Managers can leverage MFM to increase the visibility of their facility, their impact within the institution, and as a vital educational resource for scientific and administrative consultation.
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.056 | 0.025 |
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".