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Oxygen Measurement in Microdevices

2022· review· en· W4282569048 on OpenAlexafffund
Samantha M. Grist, Kevin L. Bennewith, Karen C. Cheung

Bibliographic record

VenueAnnual Review of Analytical Chemistry · 2022
Typereview
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsUniversity of British Columbia
FundersMitacs
KeywordsOxygen sensorMicroscale chemistryBioprocessNanotechnologyComputer scienceOxygenProcess engineeringBiochemical engineeringMaterials scienceChemistryEngineeringChemical engineering

Abstract

fetched live from OpenAlex

Oxygen plays a fundamental role in respiration and metabolism, and quantifying oxygen levels is essential in many environmental, industrial, and research settings. Microdevices facilitate the study of dynamic, oxygen-dependent effects in real time. This review is organized around the key needs for oxygen measurement in microdevices, including integrability into microfabricated systems; sensor dynamic range and sensitivity; spatially resolved measurements to map oxygen over two- or three-dimensional regions of interest; and compatibility with multimodal and multianalyte measurements. After a brief overview of biological readouts of oxygen, followed by oxygen sensor types that have been implemented in microscale devices and sensing mechanisms, this review presents select recent applications in organs-on-chip in vitro models and new sensor capabilities enabling oxygen microscopy, bioprocess manufacturing, and pharmaceutical industries. With the advancement of multiplexed, interconnected sensors and instruments and integration with industry workflows, intelligent microdevice-sensor systems including oxygen sensors will have further impact in environmental science, manufacturing, and medicine.

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 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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.051
GPT teacher head0.322
Teacher spread0.271 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations18
Published2022
Admission routes2
Has abstractyes

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