MétaCan
Menu
Back to cohort
Record W2099541966 · doi:10.1109/icsens.2010.5690678

Platform for all-polymer-based pulse-oximetry sensor

2010· article· en· W2099541966 on OpenAlexaff
Yindar Chuo, Badr Omrane, Clint Landrock, Jasbir N. Patel, Bożena Kamińska

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer sciencePulse oximetryPulse (music)Materials scienceComputer hardwareTelecommunicationsMedicineDetector

Abstract

fetched live from OpenAlex

The high risk of fatal infections via inappropriately disinfected medical equipment in operative scenarios are progressively prompting for better sterilization procedures in reusable equipment. The cost for thoroughly decontaminating skin-contact medical equipment such as finger-tip pulse oximeters after each use can cost hospitals several dollars per use per device; however, disposable pulse oximeter sensors at appropriately low cost can significantly alleviate healthcare expenses while virtually eliminating the risk of infections. A polymer-based pulse oximeter sensor unit that can replace traditional reusable finger-tip sensors is proposed. The unit consists of an organic photosensor module co-fabricated with an organic light-emitting-diode module under a single process on a polymer substrate. The platform is lightweight, flexible, robust, and potentially recyclable. The design considerations, architecture, and preliminary device performance results are presented. The all-polymer nature of the system promises opportunity to manufacture disposable pulse oximeter sensors at favorably low costs to replace traditional sensor clips.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.019
GPT teacher head0.246
Teacher spread0.227 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Sensor and Energy Harvesting MaterialsFrench-language works237,207