Nanoelectrospray emitters: Trends and perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The benefits of electrospray ionization are many, including sensitivity, robustness, simplicity and the ability to couple continuous flow methods with mass spectrometry. The technique has seen further improvement by lowering flow rates to the nanoelectrospray regime (<1,000 nL/min), where sample consumption is minimized and sensitivity increases. The move to nanoelectrospray has required a shift in the design of the electrospray source which has mostly involved the emitter itself. The emitter has seen an evolution in architecture as the shape and geometry of the device have proved pivotal in the formation of sufficiently small droplets for sensitive MS detection at these flow rates. There is a clear movement toward the development of emitters that produce multiple Taylor cones. Such multielectrospray emitters have been shown to provide enhanced sensitivity and sample utilization. This article reviews the development of nanoelectrospray emitters, including factors such as geometry and the manner of applying voltage. Designs for emitters that take advantage of multielectrospray are emphasized.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it