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Record W4414440553 · doi:10.1016/j.ohx.2025.e00702

Open source inert gas glove box

2025· article· en· W4414440553 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHardwareX · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGloveboxInert gasInertOpen sourceEnclosureVolume (thermodynamics)Open source hardware

Abstract

fetched live from OpenAlex

A glove box is a controlled environment used for a wide range of scientific experiments. While glove boxes provide significant advantages, their high economic costs ranging from over $1,000 to over $15,000 limits their accessibility in under-resourced labs. There are lower-cost DIY designs available on the internet, but they have not been well characterized nor validated. To overcome these limitations, in this study, an open source glove box design is developed for scientific applications using readily available components and digital distributed manufacturing using open-source RepRap-class 3D printers. The ability of the glove box to hold an inert atmosphere is quantified using an oxygen analyzer. The open source glove box can be customized to the dimensions of the user and the volume of the experiment. The design also enables the use of customizable transfer chambers that can be adjusted based on the scientific application. The open source glove box is built from a low-cost enclosure while preventing contamination. The highly portable device can reduce oxygen down to 19 ppm using an inert gas. The economic savings of the validated device compared to proprietary systems is over 95 %.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.257
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it