Piezoelectric driven non-toxic injector for automated cell manipulation.
Bibliographic record
Abstract
Stimulated by state-of-the-art robotic and computer technology, Intra Cytoplasmic Sperm Injection (ICSI) automation aims to scale and seamlessly transfer the human hand movements into more precise and fast movements of the micro manipulator. Piezo-drill cell injection, a novel technique using piezo-driven pipettes with a very small mercury column, has significantly improves the survival rates of ICSI process. It is found that complications are due, in large part, to toxicity of mercury and the damage to the cell membrane because of the lateral tip oscillations of injector pipette. In this paper, a new design of piezo-driven cell injector is proposed for automated suspended cell injection. This new piezo-driven cell injector design centralizes the piezo oscillation power on the injector pipette which eliminates the vibration effect on other parts of the micromanipulator. Detrimental lateral tip oscillations of the injector pipette are attenuated to a desirable level even without the help of mercury column. This mercury-free injector can sublime the piezoelectric driven injection technique to completely non-toxic level with great research and commercial application in gene injection, in-vitro fertilization, ICSI and drug development.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".