Open source scientific bottle roller
Bibliographic record
Abstract
Proprietary bottle rolling systems automate some laboratory applications, however, their high costs limit accessibility. This study provides designs of an open source bottle roller that is compatible with distributed digital manufacturing using 3-D printed parts and readily-available commercial components. The experimental results show that the open source bottle roller can be fabricated for CAD$210 (about USD$150) in materials, which is 86% less expensive than the most affordable proprietary bottle roller on the market. The design, however, is more robust with enhanced capabilities. The design can be adapted to the user's needs, but is already compatible with incubators with a low profile (dimensions 50 cm x46 cm x8.8 cm) and capable of being operated at elevated temperatures. The systems can be adjusted to revolves from 1 to 200 RPM, exceeding the rotational speed of most commercial systems. The open source bottle roller as tested has a capacity greater than 1.2 kg and can roll twelve 100 mL bottles simultaneously. Validation testing showed that it can operate for days at 80 RPM without human intervention or monitoring for days at both room temperature and elevated temperatures (50 °C). Future work includes adapting the designs for different sizes and for different fabrication techniques to further reduce costs and increase flexibility.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.019 |
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".