MétaCan
Menu
Back to cohort
Record W3192989385 · doi:10.1016/j.ohx.2021.e00223

An open-source powered and ergonomic personal protective respirator for frontline COVID-19 response

2021· article· en· W3192989385 on OpenAlexafffund
Emanuel Martinez Villanueva, Rafiq Ahmad

Bibliographic record

VenueHardwareX · 2021
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesUniversity of Alberta
KeywordsRespiratorPersonal protective equipmentFace shieldCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakOpen sourceComputer scienceAeronauticsSimulationEngineeringMedicineOperating systemHealth careMaterials science

Abstract

fetched live from OpenAlex

Intending to shield front-liners who are currently exposed to COVID-19, and because of the lack of proper powered air-purifying respirator, this study shows the design and development of an open-source ergonomic respirator with a washable filter. This device has an estimated working time of 12 h, and the tests' airflow always showed a value over 4.5 cubic feet per minute, a higher value than the national institute for occupational safety and health specification for full-face closed respirators. The proposal relies on 3D printing technology for all the custom-design parts and usages easy-to-access components for the rest of the material. The mask for the APRPAPR in the article has a defogging feature, 180 degrees of viewing angle, an ergonomic profile, and no obstruction on the mouth to show the user's full face. This respirator has an estimated cost of 318 USD, approximately one-third of the market's price of well-known brands.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.004

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 head0.038
GPT teacher head0.342
Teacher spread0.304 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueHardwareXSame topicInfection Control and VentilationFrench-language works237,207