High-Resolution Bulgeless Liquid-Cell Electron Microscopy
Bibliographic record
Abstract
Liquid cell electron microscopy (LCEM) has long suffered from irreproducibility and its inability to confer high-quality images over a wide field of view. LCEM demands the encapsulation of the in-liquid sample between two ultrathin membranes (windows). In the vacuum environment of the electron microscope, the windows bulge, drastically reducing the achievable resolution and the usable viewing region. Herein, we introduce a shape-engineered nanofluidic cell architecture and an air-free drop-casting sample loading technique, which combined, provide robust bulgeless imaging conditions. We demonstrate the capabilities of our approach through the study of in-liquid model samples and quantitative measurements of the liquid layer thickness. The presented LCEM method confers high throughput, lattice resolution across the complete viewing window, and sufficient contrast for the observation of unstained liposomes, paving the way to high-resolution movies of biospecimens in their near native environment.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".