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Record W2057109277 · doi:10.4236/eng.2013.55b009

Development of Wearable Semi-invasive Blood Sampling Devices for Continuous Glucose Monitoring: A Survey

2013· article· en· W2057109277 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

VenueEngineering · 2013
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWearable computerMicroactuatorBlood samplingSampling (signal processing)Continuous monitoringBlood glucose monitoringComputer scienceBiomedical engineeringMedicineEmbedded systemEngineeringArtificial intelligenceDiabetes mellitusTelecommunicationsOperations managementInternal medicine

Abstract

fetched live from OpenAlex

Semi-invasive blood sampling devices mimic the way female mosquitoes extract blood from a host. They generally consist of a microneedle, a microactuator for needle insertion, a blood extraction mechanism and a blood glucose sensor. These devices have great potential to overcome the major disadvantages of several current blood glucose monitoring methods. Over last two decades, extensive research has been made in all of these related fields. More recently, several wearable devices for semi-invasive blood sampling have been developed. This review aims at summarizing the current state-of-the-art development and utilization of such wearable devices for continuous monitoring of blood glucose levels, with a special attention on design considerations, fabrication technologies and testing methods.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.822

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 head0.017
GPT teacher head0.213
Teacher spread0.196 · 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