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Record W3095083641 · doi:10.1002/aisy.202000200

Inverse Pneumatic Artificial Muscles for Application in Low‐Cost Ventilators

2020· article· en· W3095083641 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.

Bibliographic record

VenueAdvanced Intelligent Systems · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMechanical ventilatorMechanical ventilationTidal volumeVolume (thermodynamics)Artificial respirationPipeline (software)Ventilation (architecture)Range (aeronautics)Computer scienceAutomotive engineeringMechanical engineeringEngineeringMedicineAnesthesiaRespiratory systemPhysics

Abstract

fetched live from OpenAlex

The procurement and maintenance cost of high‐end ventilators preclude their stockpiles sufficient for the mass emergency situations. Therefore, there is a significant demand for mechanical ventilators in such situations. Herein, a low‐cost, portable, yet high‐performance design for a volume‐controlled mechanical ventilator is proposed. Pneumatic artificial muscles, such as air cylinders, are used in the inverse mode of operation to achieve mechanical ventilation. With the current design, the two fundamental modes of operation (controlled mode and assisted mode) are demonstrated. Unlike most intensive care unit ventilators, the proposed device does not need a high‐pressure air pipeline to operate. The device is capable of mechanical ventilation for respiration rate ranging from 10 to 30 b min −1 with a tidal volume ( VT ) range of 150–1000 mL and the I:E ratio of 1:1–1:5. A total cost of less than $400 USD is achieved to make one device. The cost to produce the device in larger volumes can be estimated to be less than $250 USD.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.545
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.253
Teacher spread0.222 · 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