Open Source 3D Printed ISO 8655 Compliant Multichannel Pipette
Bibliographic record
Abstract
Multichannel pipettes are used widely to accelerate research and testing in life sciences laboratories and within the biomedical industry. Commercial multichannel pipettes cost several hundred to thousand U.S. dollars and are not accessible in many areas. This study utilizes an open source and digital distributed manufacturing model to design a USD$24 4-channel 200 micro-liter pipette. The design uses widely-available interchangeable off-the-shelf parts and custom components, which can be fabricated with a low-cost fused-filament RepRap-class desktop 3D printer. The manuscript describes the design, construction, and validation of an ergonomic open-source multichannel pipette, as well as the evaluation of pipetting parameters and quality control. The open source multichannel pipette is found to be compliant with ISO 8655 standards for precision and accuracy. The device has separate syringes that operate individual tips, which prevents cross contamination of specimens because there is no direct contact of different liquids with each other and no mixing with actuating air. Each syringe is easily replaced for different experiments and the source CAD files are provided to enable others to build variants or custom configurations of the open source multichannel pipette. Metadata Overview Main design files: https://osf.io/9tn6e/ Target group: chemistry, biochemistry, biology, biomedical, medical, and associated disciplines Skills required: desktop 3D printing – easy, mechanical assembly – easy Replication: https://www.appropedia.org/Open_Source_3-D_Printed_ISO_8655_Compliant_Multichannel_Pipette for comments and feedback. See section “Build Details” for more detail.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.027 |
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".