Leveraging Flexible Pipette-based Tool Changes to Transform Liquid Handling Systems into Dual-Function Sample Preparation and Imaging Platforms
Bibliographic record
Abstract
In this study, we present an advanced system that integrates simultaneous pipetting and in-situ imaging using the Opentron OT-2 liquid handling robot. This system enables real-time monitoring and characterization of dynamic processes, such as hydrogel crosslinking, without any manual intervention. The platform’s modular design maintains cost-effectiveness and high-throughput capabilities while expanding the versatility of the OT-2 robot by incorporating imaging functionalities into the experimental workflow using a pick-and-place apparatus. Due to its modular architecture, based on an OT-2 robot, the system can be adapted for a wide range of laboratory applications at an affordable cost. This real-time imaging solution offers a practical approach to laboratory automation, leading to more efficient and data-driven experimentation. Although ionically crosslinked hydrogels were used as a proof-of-concept, this platform has potential applications across various materials systems, including crystallization dynamics, polymerization kinetics, and drug delivery system 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".