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Record W2096653575 · doi:10.1186/1687-3963-2012-10

An advanced physiological data logger for medical imaging applications

2012· article· en· W2096653575 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEURASIP Journal on Embedded Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUSBComputer scienceData loggerBluetoothComputer hardwareWirelessEmbedded systemInterface (matter)TelemetrySoftwareOperating systemTelecommunications

Abstract

fetched live from OpenAlex

The interest of physiological data sensing and recording using wireless body sensor network has increased in recent years due to the advancement of miniature and portable electronic devices. In this study, the design of a portable and rechargeable data logger with high data rate multiple wireless connectivity (Bluetooth and 2.4-GHz radio frequency) is discussed. The data are logged in micro secure digital (SD) cards and can be transferred to PC or Smartphone using SD card reader, USB interface, or Bluetooth wireless link. Analog signals can also be logged through an 8-channel analog-to-digital interface. A graphical LCD with touch screen is added for control and diagnosis. The hardware is generic and targeted for various medical imaging and data collection applications. The functionality of the prototype is later tested for wireless capsule endoscopy and skin temperature logging application.

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)0.001
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 score0.914
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.317
Teacher spread0.283 · 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